Anthropic’s watermark scheme is the focus of so much discussion that you could be excused for thinking there was nothing else to talk about. For many, it’s the solution to identifying all those evil-doers who offload their writing to large language models. But we are wasting far too much time trying to determine whether (and to what degree) AI was involved in creating content. Much more important is determining whether the content was crafted with respect for the reader, and whether the creator can stand by every word. That’s the idea behind the new AI writing policy from the software company Clay, which makes far more sense than trying to detect a watermark.

Links from this episode:

• Clay AI Writing Policy: 4 Guiding Principles
• How Claude marks AI-generated content
• Anthropic’s watermark survives copy-paste, but not the real dev workflow
• Can Anthropic’s invisible watermarks curb ‘AI slop’? Researchers remain sceptical
• Anthropic’s text watermarks signal new front in AI detection
• Claude’s new Scarlet Letter watermark is invisible—for now
• How to Build a Responsible AI Writing Policy
• How Claude’s text watermarking works
• Claude is now watermarking every response — here’s what that means if you use AI for writing
• I’m Begging You: Never Write With A.I.

The next monthly, long-form episode of FIR is tentatively scheduled to drop on Monday, August 24.

We host a Communicators Zoom Chat most Thursdays at 1 p.m. ET. To obtain the credentials needed to participate, contact Shel or Neville directly, request them in our Facebook group, or email [email protected].

Special thanks to Jay Moonah for the opening and closing music.

You can find the stories from which Shel’s FIR content is selected at Shel’s Link Blog. You can catch up with both co-hosts on Neville’s blog and Shel’s blog.

Disclaimer: The opinions expressed in this podcast are Shel’s and Neville’s and do not reflect the views of their employers and/or clients.

Raw Transcript:

Neville Hobson: Hi, everyone, and welcome to For Immediate Release. This is episode 526. I’m Neville Hobson.

Shel Holtz: And I’m Shel Holtz. In the last episode of FIR, we talked about workslop and the implications workslop brings to the workplace. We’re going to continue down that path today.

I’m sure you’ve all seen the headlines about Anthropic putting an invisible watermark on anything Claude writes. I want to separate what that actually does from what people have been claiming.

First, you won’t see this watermark. It’s not a “written by Claude” tag. It’s machine-readable. It survives copy and paste, and it may even survive some editing. The reason Anthropic came up with this is to comply with the transparency rules under the EU AI Act, and it applies everywhere Claude runs: the app, the API, Claude Code, Cowork, cloud providers — you name it.

You can’t paste text into a public detector and expose someone yet. Anthropic says detection tools are coming, but it hasn’t released any of them.

Here’s roughly how it works: Every time Claude generates text, it’s choosing between several equally good next words — say, “gray” or “overcast.” Normally, that choice is random. With watermarking, though, a secret cryptographic key nudges that randomness in a consistent way.

No single word looks suspicious, but across a couple hundred word choices in an article, the pattern becomes statistically detectable if you have the cryptographic key.

That’s completely different from tools like Pangram, which look for writing patterns that seem AI-like — you know, em dashes, overuse of words like “delve” or “tapestry” or “underscore,” constantly grouping things in threes. These are all things real writers do, by the way. The rule of three is nothing unique to AI, nor are em dashes. That’s why I don’t put much stock in these tools.

Anthropic’s detector doesn’t guess. It tests whether the text matches the pattern its own cryptographic key would produce.

Now, it’s particularly important to understand that a detected watermark means the content was processed by Claude. It doesn’t mean Claude wrote it. You could write something yourself, have Claude clean up the grammar, and it would still carry that watermark. Axios flagged exactly this risk for communications teams that polish a human-written press release with Claude.

It also works in reverse, by the way. Heavily edit, paraphrase, translate, or blend the text with other writing, and that watermark can disappear. Short passages may not carry enough signal to be detected at all.

So this isn’t a foolproof “Did a human use AI?” detector. Picture a reporter running a company statement through a detector and calling it AI-generated when your team actually wrote it and just had Claude do the final polish.

The watermark tells you about processing. It can’t tell you who did the thinking.

And that brings me to Clay, the software company, which just rolled out an AI writing policy. I think this is actually more important than a watermarking system.

The policy had its origins in Clay’s engineering department, but it has since gone company-wide. It’s not a ban. Brainstorming with AI, drafting, proofreading — all that’s fine.

Instead, the policy has four principles.

First, stand behind every idea and every sentence.

Second, writing is thinking.

Third, spend more time creating a document than you expect someone to spend reading it.

And fourth, longer isn’t better. And AI, by the way, notoriously pads its content.

I like this policy a lot. I like it a lot more than “Don’t use AI to write.”

Because sometimes AI writing is exactly the right call. Plenty of people are great at their jobs and bad at writing. Engineers are a great example. I’ve used engineers as an example of this before. If AI helps these people organize their explanation and turn an incomprehensible email into something readable, that’s good for everyone.

The problem is AI can make bad thinking look like good writing. This is what we were talking about last week with workslop. You give the model a thin prompt, it hands back three polished pages, and now you’ve just shifted the work of figuring out what you meant onto everyone else who has to read it. The prose looks finished, so the creator of that content feels like they’ve finished, but the thinking never actually happened.

That was how we defined workslop last week when we talked about it.

So companies don’t need an AI policy that’s focused on AI. They need one that’s focused on accountability, quality, and respect for the reader.

Cover the basics, for sure. List the approved tools. Talk about confidential information and how it gets used. Talk about fact-checking and human review and brand voice and blah, blah, blah.

But add that Clay test: Can you defend every sentence? Does it represent what you actually think? Did you verify the facts? Did you cut the padding? And did AI make the communication better, or did you just shift your effort onto your audience?

For communicators, that last question is the one to focus on. The watermark debate is going to tempt organizations to obsess over detection: Was AI used? Can we prove it? Should we disclose it?

Yeah, sometimes, I guess, that’s a fair question. But the better ones are: Is the thinking ours? Is it accurate? Does it serve the reader? And is a human willing to stand behind every word?

If we can get those things right, I’m not too worried about whether Claude helped fix a few sentences along the way, watermark or no watermark.

Neville Hobson: Hmm. We have talked about this before — this kind of weird obsession so many people seem to have with trying to figure out whether someone used AI to write a piece so they can exclaim with great glee, “Yeah, this guy wrote this. It’s 96 percent AI. He didn’t write it at all. It’s a scam, it’s fake,” blah, blah, blah.

Shel Holtz: Yeah.

Neville Hobson: We’re already seeing it happen with this. Someone wrote the other day about this, “Finally, a way to get rid of AI slop.”

What? I mean, isn’t —

Shel Holtz: No.

Neville Hobson: It isn’t going to do that. This obsession isn’t going to stop, I don’t think.

And, in fact, maybe the best thing out of the Clay principles is taking the focus away from that and moving it to the writing, to authorship, to accountability, as you point out.

The caution, I would say, is don’t obsess about this. Don’t set concrete rules that are so inflexible that you’re going to end up with writing that isn’t flexible at all.

The point, I guess, is to concentrate on the actual writing. Think about what it is that you’re writing.

So let’s move away from “Did you use AI to write this?” to something like, “What was your contribution to this?”

That, to me, is a healthier discussion to have.

There are still going to be lots of people who do the “gotcha” talk. I saw one today on LinkedIn: “I would never hire someone who uses AI to copywrite. That kind of approach isn’t for my team,” and stuff like that.

I think asking what your contribution was encourages accountability, whereas “Did you use AI to write this?” is all about concealment and policing — discovering that someone did and assuming or implying that they’ve cheated somehow.

That said, I think the point that you need to stand behind every idea and sentence is absolutely spot on. And that’s not new. We should have been doing that all along.

That’s probably the right way to approach it.

For example, don’t ask Claude to write something: “Here’s a topic. Write a 1,200-word piece arguing that communicators need to take responsibility for AI governance.”

Claude produces it, you might edit two or three sentences, and you’re done. You publish it under your name. That is substantially AI-generated writing, and the watermark is relevant.

But for what, though? So someone could say, “Gotcha”?

You don’t know what that was for. You don’t know what’s wrong with that. Has someone deceived you? I suppose, by implication, if it’s under their name, they have deceived you in that they wrote it. They didn’t; the AI wrote it.

But what’s the difference between that and, as a comparison, Grammarly or something like that, which suggests paragraph changes and you accept every single one of its recommendations? You end up with something that’s then 70 to 80 percent Grammarly, as opposed to you.

Better, though, to avoid ethical issues and accusations and all that stuff, is that you do the writing. Don’t dump the stuff on the AI. You do the writing and introduce your own thinking to this.

Have the AI — Claude or whatever it might be — check it. Ask it to proofread it. Ask it, “Is there any other angle I could have incorporated in this?” or “Do you think this is the right approach?”

I do that a lot with the stuff that I write. And I must admit, probably two out of three times, I’ll accept some of the recommendations the chatbot comes back with.

Sorry, the AI assistant comes back with. I don’t call it chatbot.

Shel Holtz: Ha ha ha.

Neville Hobson: And there I just slipped up. I did.

So I think we’ll have to weather the gotchas all the time, and so be it. But if you are confident in doing the writing, using your AI assistant as the guide for you — as, in a sense, the editor that sits by your side, the critiquer that tells you what it thinks and where you could improve this or don’t say that — follow guidelines such as Clay has done, and you should be okay.

Shel Holtz: Yeah. The piece on Clay’s writing policy makes the point, as I mentioned, that writing is thinking. Writing is the way we process our thoughts and test our thoughts.

And this is a point that I think a lot of people have made. In fact, I just read this in The New York Times. I think it was over the weekend. I think it was an op-ed that was exhorting people to please, for God’s sake, write your own stuff because we don’t want to lose the ability to think.

The problem is, I think most of these proclamations come from writers. You and I are writers, and the communities that we interact with on LinkedIn in particular are probably also writers. We’re connected to people who are engaged in communications, and hence you get the opposition to using AI to write.

But again, what about an accountant? What about an engineer?

There are so many jobs out there where being a really good writer was never a requirement when these folks were earning their degrees or their certificates. And now, because they’re in the business world, they have to communicate effectively.

So how do you go about the thinking process?

No, you don’t want to delegate it to AI. You don’t want to say, “Write an email about X” or “Write a blog post about X.” You want to think it through.

But does that mean you think it through by writing? Well, not if you’re not a writer, necessarily.

You may think it through by creating an outline, by doing a brain dump. It could even be — this is something Chris Penn talks about a lot — just recording your thoughts as audio and then uploading that file and saying, “These are my thoughts. Now turn this into a coherent email to this audience designed to produce this result.”

Then you go back and you review it and edit it so that you can defend every sentence, every word.

Again, I think this is all about respect for the reader. And if the way you demonstrate respect for the reader, knowing that you’re a terrible writer, is using AI, that’s appropriate.

If you just knock out this email, people are going to go, “What is he talking about? I don’t know what he’s trying to get at here.”

Respect for the reader is using the AI to make that message clearer, more cogent, more understandable, and more actionable.

So, again, I really like those four pillars.

And I think there undoubtedly will be ways to defeat the Claude watermark. People will come up with them. Anything that is designed to catch people is something somebody else is going to come up with a way to circumvent.

In the meantime, though, as you say, this is not a surefire way to catch somebody. It’s going to identify that Claude processed this, not that Claude wrote it.

So I think people need to calm down and start thinking about this tool in a way that provides the high-quality content that you’re trying to deliver to people — not just something polished that makes them have to figure out what you intended because it’s polished but no thinking went into it.

The thinking still has to go into it, whether Claude’s going to do the lion’s share of the writing or not.

Neville Hobson: Yeah. I mean, I think the interesting distinction is between AI-generated and AI-assisted writing. Although I add my own caveat to that, which is: Who cares?

I mean, truly, do I want to get into a discussion about that? No, I do not.

So I know the difference. I’m not evangelizing that everyone should understand and follow the difference, although it’s helpful to.

For example, using Claude, you give Claude a short prompt — it’s not Cowork, by the way; this is just the chat — and it produces an article.

You tell it, “I want to write about X, and the topic is this, and I want to achieve this. These are the points I want to make.” Maybe not even as much as that. And Claude produces, you know, a 600-word draft, and you lightly edit it.

Lightly meaning maybe you change not the syntax so much, but certain expressive words that you might use. If that’s your bag, sure. Although you would have given —

Shel Holtz: Or adding the Oxford comma.

Neville Hobson: — your AI assistant the guidance about your preference on the Oxford comma.

Shel Holtz: Presumably, yeah.

Neville Hobson: It would know.

So you do that. On the other hand, if you’ve already developed the argument, you’ve already got a clear picture in your mind, you’ve researched it, you’ve used Claude to challenge or improve your thinking, and you make the editorial decisions yourself, that’s another matter entirely.

That, I believe, is AI-assisted writing.

So, as we mentioned earlier in the discussion, the better question isn’t, “Did you use AI?” but, “What was your intellectual contribution?”

So, writing is thinking. Yeah, I don’t disagree with that. Although, again, I don’t want to get hung up on having definitions all over the place about this.

The danger is real of turning this into another policing technology, which many people are already starting to do.

I did see in Anthropic’s FAQ about watermarking where they say, in answer to the question, “How do I check if a piece of text was written by Claude?”, “We will soon be offering a watermark detection API. We’re in the process of working out the details of its implementation.”

So that’s coming.

That’ll give those gotcha people a lot more ammo to say “gotcha” a lot more, I bet. It just takes attention away from what really matters with all of this.

But, you know, like a lot of things that are new, we have to go through all this.

So my recommendation is: Don’t give it too much attention. Be sure in your own mind that what you’re doing is, in your definition, the right way of going about it. You feel confident that it is. You have guidelines to follow, such as Clay’s, for instance, so you are able to say, “Yep, these four things — I do these things in all my approaches to this.”

In which case, you can wave two fingers at the gotchas.

Shel Holtz: Yeah, and I can’t emphasize this enough: The detection is not going to be focused on whether Claude wrote this. It’s whether it processed it.

So you could have written it and then sent it through Claude for grammar, spelling, and punctuation, and the watermark will show up, even though you wrote it.

So the gotcha is, I think, a little disingenuous in a lot of cases.

I mean, it could be that somebody used it to write, for sure, but it’s not a sure thing. It’s not a lock that if the detector says, “Yes, Claude processed this,” then, “Aha! You wrote this with AI.”

Not necessarily. It doesn’t mean that at all.

Neville Hobson: But even if he did, so what? If someone says that, do I care? Not at all.

Shel Holtz: Well, and again, I come back to the engineer or the accountant who wants to be understood and is not a writer.

I think that’s where this tool shines and where we have opportunities for better clarity and better understanding in the workplace.

Do I expect my professional writers to write? Yeah, absolutely.

Do I expect my accountants to write? My lawyers? Not necessarily.

Neville Hobson: Yeah. I mean, I think there’s one other thing about this, too.

I did read Anthropic’s technical paper describing what this is and how it works. I’m going to have to actually ask Claude to simplify this — give it to me in simple terms so I can understand it well.

Shel Holtz: Ask Claude. No, better yet, ask ChatGPT to do it.

Neville Hobson: Because it talks about, for instance, let’s say you asked Claude to write a piece. You briefed Claude, it did that, you edited it, passed it back to Claude, it made some recommendations, which you implemented, including removing a chunk. You passed it back to Claude again.

You went to and fro a bit, and you might then have — let’s say it’s an article for an academic journal, for instance — passed it to a colleague, saying, “Can you review this and give me your opinion?”

They did, and you made some further changes as a result.

The end result of all of that is so muddy that Claude would have — or rather, the watermarking wouldn’t be clear as to who wrote which bits and so forth.

You could pinpoint where the words came from, but you couldn’t pinpoint who the author was.

In which case, the gotcha folks are not going to be happy with that. But, you know, just get on with it, for God’s sake, and stop all this stuff.

Shel Holtz: Yeah. And you don’t know which words it selected to accommodate this watermarking. If your edit changes them, then the watermark vanishes.

So again, no guarantees here at all.

This is compliance with the EU AI law. That’s all it is.

By the way, I think you can expect to see the other frontier models follow suit, also to be in compliance with the EU AI law.

So the fact that only Anthropic is doing this so far —

Neville Hobson: Undoubtedly.

Shel Holtz: — doesn’t mean that you won’t see it in ChatGPT and Gemini and even maybe Grok. We’ll see.

Neville Hobson: Yeah. I mean, they talk about retrofitting this to earlier versions of Claude, and that makes total sense to me.

You are right. I believe it would make no sense if Claude was the only one doing this. So we’ll expect news from the others.

But in the meantime, my suggestion to everyone is: Don’t worry about this. Be true to yourself.

Read Clay’s guidelines — what are they called? I can’t remember. It’s kind of a policy, writing policy.

Shel Holtz: Yeah, policy. Writing policy. AI writing policy, yeah.

Neville Hobson: Okay.

And there’ll be others adding to this and saying, “Here’s my version,” and so forth. So you can pick what’s best.

But just focus on your writing.

One of the points that comes out of this is absolutely right: You do the writing. Don’t just say, “Give me a 1,200-word article on whatever topic.”

That’s the best approach, and that has been the case since before this topic emerged.

Shel Holtz: And that will be a 30 for this episode of For Immediate Release.

The post FIR #526: Forget Anthropic’s AI Watermark. Can You Defend Every Sentence? appeared first on FIR Podcast Network.

We have been hearing about work slop for a while now, and evidence is mounting that it can create long-term problems for companies. Yet we are hearing very little (if anything) about what businesses are doing about it. There’s new research, which Neville and Shel discuss in this episode, along with some thoughts about actions companies can take.

Links from this episode:

• Why People Create AI “Workslop”—and How to Stop It
• Navigating AI in the Workplace: 2026
• Harvard Business Review warns AI ‘workslop’ is rotting companies from the inside
• Botsitting, botshitting, and the hidden human labor of AI at work
• 27 Seconds to Breach: The AI “Workslop” Tax Hitting 2026 Bottom Lines
• How to Eradicate AI ‘Workslop’ From Your Office

The next monthly, long-form episode of FIR is tentatively scheduled to drop on Monday, August 24.

We host a Communicators Zoom Chat most Thursdays at 1 p.m. ET. To obtain the credentials needed to participate, contact Shel or Neville directly, request them in our Facebook group, or email [email protected].

Special thanks to Jay Moonah for the opening and closing music.

You can find the stories from which Shel’s FIR content is selected at Shel’s Link Blog. You can catch up with both co-hosts on Neville’s blog and Shel’s blog.

Disclaimer: The opinions expressed in this podcast are Shel’s and Neville’s and do not reflect the views of their employers and/or clients.

Raw Transcript:

Shel Holtz

Hi, everybody, and welcome to episode number 525 of For Immediate Release. I’m Shel Holtz.

Neville Hobson

And I’m Neville Hobson.

Shel Holtz

And Neville, it is great to have you back on the show. You’re well enough to record again.

Neville Hobson

Yeah, it’s certainly been an interesting few weeks, including the kind of disconnection that I did from just about literally everything with this heat exhaustion that I suffered, which was quite profound and far more serious than I thought, according to the doctor.

And then the R&R, as I described it—the rest and recuperation—slotted in nicely with our existing family plans here to spend some time in Novato, Marin County, in California, which we did last week. And as some listeners will know, you and I and the family, in fact, all met together, had lunch in a delightful restaurant in San Francisco last Thursday, and took some pictures, which is what people saw.

So I’m back in the UK now. It was a worthwhile visit, and, well, here we are doing FIR again. It feels like déjà vu all over again. That’s great.

Shel Holtz

It is back to normal. I should tell people that if you’re curious about the wonderful restaurant we ate at in San Francisco, it’s called Waterbar, and my company, Webcor, built the building that it’s in. So it was fun to have you there and to say, “We built this.”

Neville Hobson

Yeah, it was. I agree. The hospitality was really good in that restaurant. Very nice service, friendly people, excellent food, of course. It’s focused on fish, so if you’re a fish connoisseur, this is the place to go in San Francisco, I would say. Yeah, really nice.

Shel Holtz

Yeah, and right on the water. You get a view of the Bay Bridge and a good part of San Francisco Bay. So, yeah, it was great to see you in person. It’s been since 2019.

Neville Hobson

Yeah, a long time.

Shel Holtz

And here we are looking at each other over Riverside, but that’s not the same.

Neville Hobson

No, the next best thing, but not the same.

Shel Holtz

Yeah, being together in real life really matters. But today’s topic is one that we were planning to discuss just before you took ill, so we’re going to return to it.

Neville Hobson

Yeah.

Shel Holtz

We’re going to return to it.

Neville Hobson

We are. And this is based on an article that caught my eye a few weeks ago in the Harvard Business Review. It was actually published back in January, but having returned to it, I think it’s even more relevant than it was then.

The title of the article is “Why People Create AI ‘Workslop’—and How to Stop It.” Timely topic, I’d say. The authors use the term “workslop” to describe low-effort, AI-generated work that looks polished on the surface but ends up shifting the real work onto whoever receives it.

We’ve probably all seen examples: reports full of generic language, presentations that say a great deal without saying very much, emails that are technically fine but leave you wondering what the sender actually thinks.

Since that article appeared, the wider idea of AI slop has become much more prominent. We’re hearing the term applied to the flood of cheap, AI-generated material appearing on social networks, in publishing, marketing, and elsewhere. There’s even research suggesting that people increasingly use “AI slop” as a judgment about authenticity. Something doesn’t necessarily have to be AI-generated to be dismissed as slop; it just has to feel like it.

Perhaps the most useful new evidence comes from research by the Society for Human Resource Management, SHRM, the world’s largest professional association dedicated to the practice of human resources management. Published in June, SHRM’s Navigating AI in the Workplace: 2026, based on more than 5,000 U.S. workers, found that 41% use AI at work, and 44% of those users describe at least some of their output as AI slop. Early-career employees feel the greatest pressure to adopt AI. SHRM also found greater engagement and commitment where organizations take an open approach to AI integration.

What interested me most about the HBR article was its argument about why workslop happens inside organizations. The authors suggest that it isn’t fundamentally an AI problem at all. It’s a leadership problem.

Many organizations are telling employees simply to use AI without defining what success looks like, without giving people sufficient guidance or confidence, and without creating an environment where it’s safe to experiment, ask questions, or admit uncertainty.

In that environment, people can end up optimizing for appearing to use AI rather than actually using it well. Putting it simply, the article says it’s the result of unclear AI mandates and overwhelmed teams. Leaders are issuing vague directives for employees to start using extremely powerful tools, while many of those employees are overburdened, psychologically depleted, and operating in environments where it doesn’t feel safe to admit uncertainty or ask for help.

Evidence published since the HBR article seems to reinforce rather than undermine that argument. We’re seeing more research showing significant numbers of employees encountering poor-quality, AI-generated work while, at the same time, employees are under increasing pressure to demonstrate that they’re using AI.

There’s another dimension to this that I think is particularly interesting: productivity.

Imagine that something that previously took me two hours to produce now takes me 20 minutes with AI. That’s a significant productivity gain for me. But suppose I send it to Shel—to you—and you then spend an hour trying to understand what I mean, checking my claims, and correcting some mistakes that I hadn’t spotted. Have we actually improved productivity, or have I simply transferred the cost of my work to Shel?

That’s essentially what workslop does. And some recent research into AI-assisted work describes this as a kind of tragedy of the commons. Individuals can appear more productive while imposing additional costs on everybody else.

If an organization measures AI adoption, output volume, or individual efficiency rather than the performance of the whole system, workslop might actually look like successful AI transformation.

That struck a chord because it echoes something we’ve discussed on FIR more than once. Whenever we hear stories about AI failing in organizations, the technology itself often isn’t the real issue. AI has a remarkable ability to expose weaknesses that were already there: unclear leadership, poor communication, lack of trust, unrealistic expectations, and organizations measuring activity rather than outcomes.

And there’s an important question of individual responsibility here, too. Poor leadership may create the conditions for workslop, but that doesn’t absolve the person who sends it. If I knowingly send something I haven’t properly considered or checked simply because an AI produced it, that’s also a failure of professional judgment.

So perhaps workslop isn’t really the diagnosis at all. Perhaps it’s a symptom.

Is AI creating a new workplace problem, or is it simply shining a very bright light on old management problems? What happens when leaders measure AI adoption instead of better decisions, better collaboration, and better business outcomes? And as AI makes producing apparently polished work almost effortless, does human judgment actually become more important rather than less?

The Harvard Business Review article may now be seven months old, but the questions it raises are becoming more urgent, not less. Shel?

Shel Holtz

Without question. And there—

Neville Hobson

Mm.

Shel Holtz

—there is newer research. I found work done by the Work AI Institute. They did a 2026 research project called The Work AI Index. And in addition to workslop, they have a new term in there called “botshitting.” I kid you not.

Neville Hobson

Ha ha ha.

Shel Holtz

Botshitting describes employees knowingly shipping AI output they believe is wrong. And 12% of employees who were surveyed for this research admit to doing this. Interestingly, when they are basically caught, they blame AI. They say, “The AI did this.” Forty percent of workers blame the AI rather than themselves.

There was also a study in January 2026 from Workday. Some 3,200 leaders found that 37% of AI productivity gains are immediately lost to rework because the workslop isn’t adequate, with employees spending an average of six hours a week correcting or rewriting flawed AI content.

Built In reported workslop now affects roughly 40% of employees and costs about $186 per worker per month. And there was a more recent study—BetterUp sourced this figure—that found that 66% of workers are spending six-plus hours every week fixing AI errors. So this is serious stuff.

And by the—

Neville Hobson

Mm.

Shel Holtz

—way, nearly every recent report on workslop ties this to layoffs associated with AI. Workers and outlets are connecting 2026 tech job cuts to premature AI-driven headcount reduction. And the workers who are left behind are absorbing that workslop rework burden. So we cut people to use AI; now the survivors are—

Neville Hobson

Mm.

Shel Holtz

—cleaning up after it. That’s an important framing to look at.

And one last thing I’ll mention from some research—this was just from June of this year. They found that the errors in workslop go beyond the work that somebody else needs to do to correct it. It moves downstream through teams and into the organization’s collective knowledge base. And that knowledge base just deteriorates.

So it’s not just individual wasted hours, but this slow erosion of what the organization actually knows to be true. This is a very serious problem, and I don’t see a lot being said about measures that organizations are taking to address it. I think some measures need to be taken pretty soon, or this is going to get out of control.

Neville Hobson

Yeah. The Harvard Business Review article does have some suggestions about what organizations can do to address it, which I’ll mention in a minute. But they also include some examples. I found these rather interesting. Not a whole lot—three only—but nevertheless, they talk about the toxic effect workslop can have on workplace dynamics, breeding mistrust and leading team members to think less of the sender’s intelligence and trustworthiness, among other traits.

They talk about their ongoing research, where they’ve heard a number of examples of workslop seeding ill will, eroding trust, and generally having a corrosive effect on workplace morale.

There’s one where I thought, I can imagine this. One example they give is an employee at a technology company who told the Harvard Business Review that he’d noticed the tone in his performance review was unlike his manager, and that the document recycled content from his self-evaluation. The experience made him feel unvalued and underappreciated, and he gave up all hope that he would ever be promoted.

So, reading between the lines, what happened? Whoever did that grabbed some of the employee’s self-evaluation and had an AI produce the review. I bet that’s what happened there.

We don’t know the details behind that, but that’s a really good example of what you could see happening in an environment where there is a lack of clarity, all those things the Harvard Business Review points out, and the pressure to deliver in some form or another.

So, for instance, doing an employee evaluation would come into that area where the manager has cut corners and used AI to do it. And I could imagine that is happening a lot.

And in relation to the examples that the Harvard Business Review piece includes, they say something quite interesting. Many of the responses focused on the productivity costs—the time people wasted dealing with each instance of workslop that crossed their desks. But they note that what should really worry leaders is the impact workslop can have on human relationships.

And I think that’s a point to hammer home. It’s a kind of soft thing. You don’t necessarily see it, but it’s there. And some of these examples make that very clear indeed. So that’s a manifestation of the management failure behind all of this, Shel, don’t you think?

Shel Holtz

I do. And I think it’s because we’ve been rushing headlong into this rather than pausing to strategize it.

And I think we’ve talked about that deterioration of human relationships once before. The situation is that people are not picking up the phone or sending an email off to the local subject-matter expert because Claude has the answer. ChatGPT has the answer. So you’re getting less of that interaction within the organization.

This is causing people to assume some of the work that is outside their area of expertise, outside their lane, if you will, instead of reaching out to the people in the organization who actually have that expertise so they can do the work that previously was part of their job.

Another interesting thing you noted was that somebody felt this was leading to a lack of promotion opportunity.

Neville Hobson

Mm.

Shel Holtz

I’m reading a book right now, an excellent book. We were talking about it before we started recording. It’s called Robot-Proof. And one of the things she talks about is this economic phenomenon of deprofessionalization, where AI takes on a certain amount of the work, and therefore you, as the professional, don’t need to know or do as much as you did before.

And it lowers your overall value. It pushes the wage down for people who are doing that. The author, Vivienne Ming, uses an analogy of Jiffy Lube, which in the U.S. is a place where people take their cars to have their oil changed.

And she says, “What if colonoscopies worked that way?” You don’t need a doctor to do a lot of this work because a lot of the work in a colonoscopy is pretty routine and AI can do that. Now you need just the Jiffy Lube guy there to take the hose and do—

Neville Hobson

Yeah.

Shel Holtz

—the insertion, looking at the camera to make sure it’s right. But that’s more of a technical skill than a deep medical skill that is taught in medical school and then honed over years of experience and practice.

And this is the road I think we’re headed down if we don’t take some steps to fix it. The people who were brought into an organization based on education and years of experience and subject-matter expertise, and perhaps even thought leadership, no longer need all that stuff. They just need to do the base-level effort that is required by a human following the instructions of the AI.

So I think organizations need to look at this very seriously: how this work gets done, what is required of the outputs, and having guardrails in place to make sure that people aren’t skirting around it.

Because let’s face it, if the cost of producing this stuff continues to drop, there’s an incentive on the part of the organization to go ahead and use this because the cost is lower. It’s hard to see the impact of that on sales and reputation in the short term. In the long term, I think it absolutely will have that impact.

Neville Hobson

Yeah, I’d say you’re right. I mean, one thing that I’ve been talking about all year in everything I’ve written or said about artificial intelligence in organizations is that it’s about the people, not the technology.

If we’re implementing AI or doing a rollout or planning it, or telling people, “Use AI,” as a leader, you have the responsibility to make that as crystal clear as possible and focus on the people.

So one of the things I did like about the Harvard piece was the concluding remarks they make, starting with this: “The greatest irony of all is, to make AI work at work, we need to get better at being human.”

Absolutely spot on.

Leaders need to make space for the unpolished, slower but more rewarding work of human collaboration. Without organizational changes that enable agency and trust rather than AI mandates for overburdened teams, we’ll all drown in the sludge of workslop.

A very well-put concluding statement, I think. But the serious element of that is something that, in my opinion, I’m amazed that leaders don’t seem to get at all.

They talk about efficiencies. They talk about cost savings. They talk about all these things, and yet there’s nothing about: How do we help employees become more productive themselves and develop themselves, too? How do we help them, in a sense, augment their skills using AI?

Now, that’s not to say—and I’m not suggesting for a second—that AI leaders generally just don’t think about that at all. I believe they do, but it’s way down the priority list in terms of how they communicate this. They need to get that to the top of the priority list.

But more than just talk about it, they need to put these things in place. And there are many things they can do. There’s, in a sense, rebuilding trust with people.

We’ve talked about examples in recent episodes of layoffs that are very clear to see. People are talking about them all the time, and that is happening. We talked about a really great one a few episodes back about what Ford Motor Company is doing with the graybeards. Lovely name. We’ll pass on the age—

Shel Holtz

Mm-hmm.

Neville Hobson

—thing on that. But it’s about the organizational collective memory people have of how things are done and what worked in the past, among people who were laid off and are gone.

So they rehired a whole bunch, and they’ve benefited hugely, as the articles we cited go into in some detail, including, I believe, if I recall, Shel, they were the number-one automaker for a particular reason that they attribute directly to rehiring all these graybeards.

So that is a great way of doing it. But it’s just one example. There are undoubtedly more fundamental things organizationally that people can do to rebuild this connection between the organization and the people who make up that organization—the employees, mostly.

So there’s a lot of work to be done. And yet none of this is rocket science to leaders at all, I don’t believe. Just because we’ve got this newfangled technology on the scene, you’re telling people to start using it without giving them the proper guidance.

So these, to me, are Leadership 101 things. And if no one’s doing this, then communicators, let’s step up to the plate and help. That’s what I think we should be doing.

Shel Holtz

Yeah, absolutely. And I have been reading more and more research that talks about what happens when you delegate your thinking to AI.

Rather than doing the research yourself and the writing yourself, which helps you think through the issue, it actually has an impact on your ability to think and to learn. So there are a lot of reasons I think that we need to take this seriously.

I think the first thing communicators need to do inside their organizations is raise the alarm. Because I think this may be an issue where everybody’s heard “slop” and everybody’s heard “workslop,” but I don’t know that everybody in the organization—especially the decision-makers—is up to speed on what the research is saying about all of this and the deleterious impact it can have on our organizations and the outputs that we produce.

So, yeah, I think sharing this data—and we will have links to the research in the show notes—and making the people who make the decisions aware of what this could mean to the future reputation and earnings of the organization is the place to start.

Neville Hobson

Yeah, I agree.

So, simply, there are good tips in this discussion. The links to the articles—please read them. They’re really, really useful. You’ll find a lot of insights in all the ones that we’ll have in the show notes. So there you’ve got your route map, I would say.

Shel Holtz

And that’ll be a 30 for this episode of For Immediate Release.

The post FIR #525: The Consequences Businesses Will Face from Work Slop appeared first on FIR Podcast Network.

Most companies are experiencing some level of turmoil over their adoption of Artificial Intelligence. They should be able to lean on their managers to interpret these issues at the ground level. Research, however, finds that training has left managers out. They may be getting some of the same training all employees are getting, but nothing to help them guide their teams. That will become more and more problematic as challenges continue to mount—like the two issues that have emerged recently: companies shifting the models they’re using, and employees stepping out of their areas of expertise because AI can give them information they would normally turn to internal subject matter experts for.

Links from this episode:

• ‘Tokenmaxxing’ hits limits as workplaces look for cheaper artificial intelligence
• Workers are crossing job boundaries with AI, OpenAI research shows
• Managers say they don’t feel ready to lead an AI-fluent workforce

The next monthly, long-form episode of FIR is tentatively scheduled to drop on Monday, August 24.

We host a Communicators Zoom Chat most Thursdays at 1 p.m. ET. To obtain the credentials needed to participate, contact Shel or Neville directly, request them in our Facebook group, or email [email protected].

Special thanks to Jay Moonah for the opening and closing music.

You can find the stories from which Shel’s FIR content is selected at Shel’s Link Blog. You can catch up with both co-hosts on Neville’s blog and Shel’s blog.

Disclaimer: The opinions expressed in this podcast are Shel’s and Neville’s and do not reflect the views of their employers and/or clients.

Raw Transcript:

Shel Holtz:

When companies change something they’ve been extolling for the last six months, managers are expected to support that change. When employees step outside their lane, managers are supposed to manage that. But can managers do these things when they haven’t been prepared?

That’s the case with some of the fallout from the introduction of artificial intelligence in organizations. The details are coming up in this short midweek episode of For Immediate Release.

Hi, everybody, and welcome to episode 524 of For Immediate Release. I’m Shel Holtz, and you’ve got just me again this week.

I have three artificial intelligence stories to share with you. Organizational communicators are going to have to live at the intersection of all three of these issues, whether we’re ready or not, so let’s tackle them as parts of a bigger whole.

I’ll dive into these stories right after this.

Let’s start with the whiplash.

For the past year or so, companies have been in what some have come to call the “token-maxing era”: Throw AI at everything, reward employees for burning through as many tokens as possible, and worry about the ROI later.

Nvidia’s Jensen Huang was quoted as saying that if your half-million-dollar engineer isn’t burning $250,000 in tokens, something’s amiss. Meta reportedly ran an internal competition rewarding token usage.

That was the mood last spring.

Summer’s mood is different.

The Associated Press—and, by the way, this same reporting ran in The Washington Post, The Philadelphia Inquirer, and elsewhere—describes companies now hitting a wall. Costs went up, productivity didn’t keep pace, and the bill is coming due.

We covered this in episode 517 back in early June, but just as a reminder: Uber blew through its entire annual AI budget in four months, according to its CTO, and has since rolled out spending tiers starting at $1,500 a month per employee.

Some companies aren’t just tightening budgets; they’re switching platforms entirely. One AI startup called Lindy moved 100% of its traffic off Claude and onto DeepSeek, the cheaper Chinese alternative. Its CEO told CNBC that the cost curve “crashed to the ground.”

Multiply that kind of switch across every company currently having the same conversation, and you’ve got a specific communication problem: How do you explain to a workforce that, after spending months enthusiastically evangelizing one tool, you’re now moving employees to a different one—possibly overnight—for reasons that are mostly financial and don’t actually involve the employees who have been building things on the original tool?

That’s problem number one.

Problem number two is going to make problem number one look simple, because it’s not just about which tool people use. It’s about what people are allowed to do with it.

Axios got an exclusive look at new OpenAI research drawn from more than 800,000 work-related ChatGPT messages from business users. The finding is that workers are routinely doing other people’s jobs.

Roughly 44% of occupation-specific requests involve tasks typically associated with a different profession. After stripping out generic activities such as drafting emails, customer service employees, designers, and HR professionals are the biggest boundary crossers. Something like three-quarters of their profession-specific prompts touch work that belongs to somebody else’s job title.

People are using ChatGPT to draft marketing materials, troubleshoot software, run financial calculations, and interpret regulations—jobs that used to require reaching out to a specialist for help.

OpenAI’s chief economist told Axios that the boundaries between jobs are already becoming more flexible because of this.

Now, if you’re in communications, you can probably already hear the governance questions stacking up.

Who’s accountable when a well-meaning employee uses AI to draft something that touches legal, financial, or regulatory territory in which they have no training?

What happens to your carefully built subject-matter-expert review process when everyone feels like a generalist?

And when something goes wrong because of bad advice, off-brand sentiment, or a compliance miss, who owns that failure? Is it the employee, the tool, or the manager for not seeing it coming?

That brings us to the third piece, and honestly, it’s the one that worries me most.

HR Dive reported on new research from Indeed and YouGov. The headline number is that 43% of managers say they feel poorly equipped—or not equipped at all—to lead a workforce that’s fluent in AI.

More than half of workers say they’re not getting the AI training they need. Employer expectations for what workers should be doing with AI are running two or three times ahead of what workers actually feel comfortable doing.

Indeed pointed out that companies have spent two years building AI-ready workforces. The next challenge—and arguably the harder one—is building AI-ready leaders.

Now, put these three stories together and you get a pretty clear picture.

Companies are going to keep switching models and vendors as the economics shift. Employees are going to keep wandering across job boundaries because the tools make that easy and, honestly, tempting.

The people standing in the middle of both trends—the frontline managers who must explain the switch, catch the boundary problems, and answer the “Wait, am I even allowed to do this?” questions in real time—are the group companies have prepared the least.

That is a communication problem, and it’s ours to fix.

If managers don’t understand why the company moved off the model they spent six months championing, they can’t credibly explain it to their teams. They’ll either go silent, which breeds suspicion, or they’ll improvise, which is worse.

If managers don’t have clear guardrails explaining what kinds of AI-assisted work outside someone’s lane are acceptable and what kinds require a specialist’s involvement, they’ll either rubber-stamp everything or block everything. Neither option serves the business.

And if leadership training lags this far behind workforce adoption, managers become the bottleneck at exactly the moment the company needs them to be the translators and interpreters.

Here are three things I’d be pushing for internally right now:

First, build the change narrative for platform and model switches before you need it. Develop a plain-language explanation of why these decisions happen that managers can use without having to invent their own justification on the spot.

Second, give managers an actual decision framework for cross-boundary AI use. Provide a simple test for determining when an employee’s AI-assisted work needs specialist review so managers aren’t left guessing.

Third, take the Indeed numbers to leadership. Make the case that you can’t roll out AI training for the frontline while skipping the people who manage the frontline.

It’s the difference between an AI rollout that sticks and one that quietly falls apart at the manager layer.

Thanks for putting up with a lone voice again this week. With luck, Neville will be back in the saddle next week.

As I mentioned last week, Neville and I are set to have lunch in San Francisco on Thursday. It’s the first time we’ll have seen each other face-to-face in almost seven years, if I’m remembering correctly. I’m looking forward to that. Watch for photos.

And that’s a 30 for this episode of For Immediate Release.

The post FIR #524: Are Managers Ready to Lead an AI-Fluent Workforce? appeared first on FIR Podcast Network.

Neville has been ill and unable to record, so Shel is on his own in this episode (except for Dan York’s Tech Report). This shorter-than-usual monthly long-form episode includes reports on rethinking thought leadership, maintaining “brand sovereignty” in the AI era, and whether hedging in your communication can serve a useful purpose. Dan’s report was recorded in Vienna, Austria, where AI was front and center at the 126th meeting of the Internet Engineering Task Force. Dan also reports on Bluesky’s Attie AI feature, Instagram’s plans to charge for AI access, Beehiv’s new community feature, WordPress’s plans for version 7.1, and some UK social media regulatory updates.

xx

Links from this episode:

• How Marketers Should Rethink Thought Leadership
• Treat Thought Leadership as a Lasting Asset, Not a One-Off Campaign
• A 5-Step Framework for Genuine Thought Leadership
• Why thought leadership is no longer optional for tech companies
• The ROI of Thought Leadership
• CEO thought leadership can drive $367M in value
• Why Thought Leadership Is Failing — and How to Solve It
• Reclaiming Brand Sovereignty In The AI Era
• The paid brand mention problem in GEO
• Can Hedging Make You a Better Communicator?
• Effectively communicating uncertainty: The persuasive impact of different types of hedges
• The Role of Different Markers of Linguistic Powerlessness in Persuasion
• Hedges, Tag Questions, Message Processing, and Persuasion

Links from Dan York’s Tech Report

• Bluesky’s AI assistant Attie expands into an open social research tool
• Attie: AI for the Atmosphere
• Instagram will charge for AI access
• Newsletter platform Beehiiv now lets subscribers chat with each other, adds AI
• Roadmap to 7.1
• Investigation into TikTok’s compliance with duties to protect children from encountering harmful content under section 12

The next monthly, long-form episode of FIR is tentatively scheduled to drop on Monday, August 24.

We host a Communicators Zoom Chat most Thursdays at 1 p.m. ET. To obtain the credentials needed to participate, contact Shel or Neville directly, request them in our Facebook group, or email [email protected].

Special thanks to Jay Moonah for the opening and closing music.

You can find the stories from which Shel’s FIR content is selected at Shel’s Link Blog. You can catch up with both co-hosts on Neville’s blog and Shel’s blog.

Disclaimer: The opinions expressed in this podcast are Shel’s and Neville’s and do not reflect the views of their employers and/or clients.

Raw Transcript:

Shel Holtz

It’s an unusual FIR episode today, with just me and three reports for this long-form installment.

Thought leadership isn’t what it used to be—or at least it shouldn’t be what it used to be. With AI summaries increasingly becoming the way people get the information they’re looking for, how do you maintain your brand’s sovereignty over the information that gets shared about it?

And do you hedge in your communications? There’s actually research into whether hedging is a good or a bad thing.

That’s what’s coming your way in this shorter-than-usual monthly long-form episode of For Immediate Release.

Hi, everybody, and welcome to episode number 523 of For Immediate Release. I’m Shel Holtz in Concord, California. This is our monthly long-form episode for July 2026, and I am on my own.

You may have noticed that we didn’t post a short midweek episode last week. Neville has been quite ill, with an infection in his chest and some other issues, some of them related to the ridiculously intense heat they have been suffering in England. It has kept him from being able to record.

He is planning a trip to the U.S.—here to the Bay Area, in fact. We are scheduled to have lunch on my birthday while he’s here, and right now he is focused on doing everything his doctor has told him to do so he can make that trip. That’s a decision I fully support.

It has been way too long since Neville and I have seen each other face to face in the same room. I am really, really looking forward to it. I hope you’ll join me in wishing him a speedy recovery.

Rather than skip this episode, I’ve decided to do it on my own. We used to do this fairly routinely back in the day, when both of us were full-time consultants and traveled a lot to meet with clients.

Frequently, one of us wouldn’t be available on the day we were recording. The other would record solo, or occasionally, if I had enough notice, I would find a guest co-host.

But today, you get just me.

At this point, we usually start with Neville providing a wrap-up of the episodes we’ve recorded since our last monthly long-form installment. I will take that on, along with a comment or two we have received related to those episodes.

Episode 520 was our long-form episode for June. It covered the PR meltdown that was going on among the big AI frontier labs.

There were five other topics, including one about Wowcher, a U.K. coupon company that sent an email with a promotional statement that upset just about everybody.

It was related to a young child who had been picked up and put into a crocodile enclosure and was in critical condition, the last I heard. Wowcher’s email said, “Snap up these deals quicker than a croc can catch a kid.”

Yes, if you didn’t hear the episode and you’re hearing this for the first time, this is not a joke. This is not The Onion. This was a real promotional message from the company, and it got hammered over it.

Tim Sutton left a comment saying:

“Your closing line is the whole thing, Shel. The ‘AI approved it’ defense itself is never enough. An approval step is not bureaucracy. It’s where a human asks the question no machine thinks to ask: How does this read on the worst possible day? Strip it out to move faster, and you have not saved time; you have removed the brake. I have seen the aftermath.”

Episode 521 focused on Ford rehiring people it had previously let go, ostensibly because AI would be able to do their jobs. AI was not able to do their jobs.

Rick Segal found it interesting that Microsoft, his alma mater from the 1990s, had decided to let the graybeards and their institutional knowledge walk out the door through early retirement rather than undertake the hard-core and honest “Oops, we overhired” cuts.

The decades of knowledge walking out Redmond’s door, he said, are going to be felt eventually.

Eric Carroll replied to Rick, saying:

“They will pay for replacing expertise with engines of mass satisficing. Just as you say, how long will the blast take to propagate? From what I am hearing and seeing, the return on misinvestment is way faster than I expected.”

Episode 522 was about Podcasting 2.0, a new set of protocols Adam Curry is working on with an engineering colleague named Dave Jones.

We talked about whether this would be good for podcasting and podcast listeners, the likelihood of widespread adoption, and some of the obstacles standing in its way.

Vincent Bruneau wrote:

“The slower-than-hoped-for adoption is the most interesting part of the Podcasting 2.0 story. Richer metadata, transcripts, chapters, and better accessibility are genuinely useful features. So why hasn’t it moved faster? That gap between good technology and actual adoption is always where the real communication lesson lives.”

Juraj Schaefer, a podcast producer and editor, wrote:

“Interesting perspective. As podcasting evolves, ownership, discoverability, and meaningful connections will become even more important.”

And Dakshina Senadheera, a podcast editor and manager, shared this thought:

“Interesting conversation, especially around keeping podcasting open while improving the listener experience.”

Thanks to everybody who commented on our previous episodes. You are always welcome to comment.

You can leave comments on LinkedIn, where we announce the episodes, as everybody whose comment I read today did.

You can also send us an audio or text comment by email at [email protected]. You can record a comment directly from the FIR website, FIRPodcastNetwork.com, by clicking the “Send Voicemail” button on the right-hand side of the screen.

Or you can leave a comment in our show notes. There are all kinds of ways you can comment and participate in the show.

I also want to let you know that the interview we did with Pete Blackshaw about the Answer Economy is now available.

It has been getting some really good reactions. People have found real value in this discussion about how AI answers are now the answers people are getting about your product, regardless of where the information the frontier models accumulated came from.

You can find that in FIR Interviews.

The latest episode of Circle of Fellows is also available. Episode 131 is about the evolving media landscape and what it means for media relations.

Our panelists included Diana Degan, a new IABC Fellow from the 2026 class of Fellows, along with Ned Lundquist, Martha Muzychka, and Jennifer Wah.

They talked about whom we reach out to when there are fewer reporters available to tell our stories through the mainstream and trade press we have been accustomed to.

The next episode, coming up on the third Thursday in August at 6 p.m. Eastern, is about AI and the kinds of pivots communicators will have to make as AI becomes a more widely used tool in the communication toolkit.

The panelists will be Bonnie Caver, Adrian Cropley, Theomary Karamanis, and Mike Klein. I’m looking forward to that.

Now I have three reports, as I usually do in the monthly long-form episode of FIR. You just don’t get three from Neville.

As I mentioned earlier, this is going to be a shorter episode than usual.

Two pieces landed in the search press recently that I think belong together, even though they were written a few weeks apart by people who probably weren’t talking to each other.

The first is by Bill Hunt at Search Engine Journal. Search Engine Journal has been around a long time and has been a great source of information about search and adjacent topics.

Hunt points out that, for 20 years, digital strategy meant driving people to webpages. We deliberately fragmented our information across dozens of pages, each optimized for a different stage of consideration.

The example Hunt uses is Ford and its F-150 pickup truck.

The homepage sells the lifestyle. Model pages introduce the trim levels. A configurator lets you picture yourself owning it. Feature pages handle towing and off-road performance. Specifications live even deeper in the site, next to regional offers and financing.

For a human being, that architecture is beautiful. Every page does a job.

For a machine, it’s just friction.

When an AI can’t find a dense, complete answer on your own domain, it doesn’t give up. It assembles the best answer it can from whatever is easiest to retrieve.

Consider the story that broke last week about an OpenAI model escaping from its sandbox and hacking its way into Hugging Face.

What was it looking for? It was looking for the answer sheet—the cheat sheet for the test it had been told to solve.

Rather than do the work to solve the test, it went hunting for the cheat sheet that had all the answers in one place.

That’s no different from this.

Hunt searched for the gas mileage of an F-150 Raptor. The AI Overview built its answer from Reddit, an automotive publisher, and a local dealership. It never touched the Ford website.

Ford has that number. Ford has every number.

Gemini just found it easier to assemble an answer from somewhere else where all that information was in one place.

Hunt calls the thing you’re trying to protect “brand sovereignty”: your ability to remain the authoritative source about your own products, services, and expertise, no matter where the answer eventually gets delivered.

He is emphatic that this is not a search engine optimization problem. It is a governance problem, because no single team owns the whole picture.

Product information, documentation, customer support, legal policy, and commerce are all owned by different parts of the organization. All of them shape how your organization gets represented, and they have been evolving independently for years.

His summary line is one I would hang on my wall: Your website is no longer your digital asset. Your knowledge is.

Communicators have spent 30 years arguing that the corporate website is the front door.

Hunt’s case is that the front door is now a machine reading whatever knowledge it can find. If yours is scattered across content management systems, PDFs, and support portals, the machine will find the gaps—and it will fill them from Reddit.

Meanwhile, Gaetano DiNardi, writing in Search Engine Land—not Search Engine Journal, but another great, longstanding search-focused publication—looked at what is being sold to companies that want to fix exactly this problem.

Once the industry decided that off-site brand mentions drive AI visibility, a market miraculously appeared to sell them. He audited several highly rated vendors selling brand-mention services.

What they are selling turns out to be variations on one thing: renting space on websites nobody reads.

Some of it involves placement on what the SEO world calls private blog networks. These are clusters of sites that exist for no purpose except to sell mentions and links to whoever is willing to pay for them.

DiNardi found those going for 10 to 15 times what a comparable link cost in the old SEO market.

Some of it involves placement on sites with no actual subject-matter focus.

One example he cites has a page about learning-management software sitting alongside listicles ranking the best crypto wallets. That is basically a billboard that will print anything.

Some of it is Reddit astroturfing.

Agencies use what are called aged accounts—profiles built up over months so they look like real community members—and use them to post brand mentions in subreddits that have nothing to do with the brand.

Those posts are frequently removed within 30 days for violating community rules, which tells you exactly what the communities make of them.

Then there are the mechanics.

There is a Slack workflow. The agency generates a placement opportunity. A junior marketing assistant with no way to evaluate whether the publisher is legitimate approves a fee.

In DiNardi’s example, that fee is $250 to add the mention. The agency pays the publisher and then invoices the client to recover it, on top of the retainer.

The Federal Trade Commission’s endorsement guides—and that is a U.S. agency, so these are applicable only in the U.S.—require clear disclosure of paid placements.

These pages generally are not updated to say that the mention was purchased.

Lily Ray, who is quoted in the piece, says this is another evolution of spammy link-building. We have seen this movie before, going back to Google’s first Penguin update in 2012.

The reason it appears to work right now is that large language model citation systems are still immature compared with Google’s spam detection.

Volume from low-quality sources may be rewarded in ways it would not be in old-school search.

DiNardi puts that window at perhaps one to two years before the platforms build countermeasures. He also notes that marketers chasing volume may be confusing the models about their own entities in the process.

Here is why I mashed these two stories together: They are the legitimate and illegitimate answers to exactly the same question.

Who controls what the machine says about us?

One answer says: Organize your knowledge so you are the most useful source available.

The other says: Pay strangers to say your name.

The first is a governance project, and it is the one you should be focusing on rather than waiting to be invited to participate.

Nobody else in the building has responsibility for how the organization is represented as a whole. That is within the purview of the communication function.

The second is going to show up on your desk as a pitch or proposal, probably coming from the marketing department, probably with a persuasive percentage attached to it, along with a deadline.

When it does, the questions you should ask are the old ones.

Is it disclosed?

Would we be comfortable if a reporter published the invoice?

Are we buying a spot on a page that also sells spots to our competitors?

We spent a couple of decades getting pay-for-play out of media relations. I would hate to watch us import it into AI visibility just because the metric is new.

Dan York

Greetings, Shel, Neville, and FIR listeners all around the world. It’s Dan York coming at you from Vienna, Austria, where I’ve been attending the 126th meeting of the Internet Engineering Task Force, or IETF.

These are the engineers and others who make the internet work through all the various protocols—HTTP, email, and all those kinds of things.

One of the big topics this week, of course, was AI. There were a number of sessions looking at what kind of work needs to be done.

For instance, in a world where everybody talks about “agentic, agentic, agentic, agentic,” do we need new protocols for communicating when an agent goes to book airfare and interact with all sorts of systems? Are new protocols needed?

Part of the genius of the internet is that it is built from small building blocks that can be used to do things and then reused in many different ways.

One of the things people are finding is that many of the existing protocols work well. But we are still trying to figure out, in this new world, what is happening and what new things are needed.

One thing happening in the standards world is the same thing we are seeing throughout the rest of the communication world: a lot of slop.

There is a positive side to this. The IETF conducts all of its work and develops all of its standards in English. If you are not an English speaker, or English is not your primary language, it can be challenging to help create new standards.

Back in the early 2000s, before we had all these new tools, I helped some people for whom English was not their primary language. It was painful because they were trying to create standards and describe how they worked, but their English was difficult to read. I helped them improve it.

Now, with these tools, people can contribute in English. They can put their material into the large language model of their choice and get good English back in the format of an internet draft or standard.

That is the positive side. Suddenly, millions or billions more people around the world are able to participate in the standards process in English.

The negative side, of course, is that people are generating so many contributions that they take a long time to triage. This creates a tremendous amount of work for reviewers, leaders within the IETF, and others. Everything is taking much longer.

We have seen this in many other areas. Put up a job advertisement and you get a bazillion applications. Publish a blog post and you get a ton of comments. All these things are happening.

One thing I had not paid as much attention to was the fact that all these email tools now have a feature that says, essentially, “Write a better email.”

People are using that feature, turning what might have been short, not particularly well-worded emails into big, voluminously long messages. That is generating a lot more traffic on the email lists people use within the IETF.

It gets us back to the situation we have seen many times: You have five bullets, feed them into an LLM, and it generates a long block of text. Then the text is too long for someone to read, so they use another LLM to turn it back into five bullets.

There we are, with the snake eating its tail.

There have been a lot of interesting conversations. We’ll see where all this goes.

Speaking of AI, a couple of other things have happened in the broader industry.

First, you may or may not have noticed that Bluesky announced Attie—A-T-T-I-E—its AI assistant. It started as something you could use to build social feeds within the Atmosphere, the broader AT Protocol ecosystem.

You could use Attie to create these feeds. Bluesky has now announced that it is expanding Attie into more of a chatbot that you can ask for information and news from across the broader Bluesky network—the Atmosphere, as it is called.

I don’t have access yet. I’m on the waiting list.

They say these are not chats. They are “quests.” Yes, you heard that right. They are quests—a new way to explore the Atmosphere.

You could ask questions such as, “What’s trending in my network today?” “Who’s worth following in climate tech?” or “Put together a daily briefing on indie game development.”

We will have to see what this looks like, how it works, and all those kinds of things. But it is another example of AI coming into the Bluesky space.

AI systems, of course, cost money to operate. Instagram chief Adam Mosseri has said this is really expensive and that the company will eventually have to throttle people or ask them to pay.

If you are a communicator who has been using Instagram’s built-in AI to generate campaign content, create images, or perform similar tasks, casual use is still free right now.

At some point, however, if you use it at high volume, you will probably wind up being charged for credits or have to take those costs into account.

Stay tuned on that.

Switching to newsletters—but remaining on the subject of AI—Beehiiv, B-E-E-H-I-I-V, one of Substack’s competitors, had a major release this month.

It rolled out something called Communities, which lets you create a community around your newsletter that people can join, where they can chat with one another and do those kinds of things.

At the same time, Beehiiv added AI components, including an AI assistant that can help you examine your content and subscribers, particularly on the administrative side.

Again, we are seeing more AI appearing in different places.

Speaking of AI—as that seems to be the theme of my report this month—I’ll also tell you that WordPress 7.1 is currently scheduled to arrive on August 19, before my next report. The timing aligns with WordCamp US here in the States.

The release will bring a number of new features, including more of the collaboration functionality that was part of the original plan for WordPress 7.0.

It will include notes and other features, along with more collaboration and AI elements. That is coming on August 19.

Finally, let me close with a policy topic.

The U.K.’s Ofcom is pursuing two different initiatives. It has announced a forthcoming ban on anyone under 16 using social media. I’m not entirely sure what that means in practice.

It has also announced that it is investigating TikTok’s compliance because it does not believe the platform did enough to prevent people under 13 from using it.

This will be a test of the U.K.’s law, so we will see where it goes when it reaches the courts.

There is also a proposal under which people younger than 16 would be banned from social media, while 16- and 17-year-olds would somehow magically be blocked from using social media between midnight and 6 a.m.

It remains to be seen how any of that can be turned into reality.

The other problem people have pointed out is that all you are doing is blocking children from seeing some of the harmful material. You are not actually getting rid of the terrible content on the internet.

Everybody else is still exposed to it, including seniors and others who may have as many issues and challenges with it—if not more—than some of the young people in that space.

Anyway, that’s all from here, Shel. I think I’ll go get some Wiener schnitzel and a beer.

Until next month, that’s all. Back to you.

Bye for now.

Shel Holtz

Thanks, Dan. I really enjoyed that report. I was particularly struck by two of the items that you reported on. The first was Addy for Blue Sky. I just really like the idea of using AI this way within social networks. That would come in so handy if I could do that with, say, LinkedIn, rather than use the current search tool, which is fundamentally worthless unless I’m just looking for a person.

Or a company, but if I’m looking for threads around certain topics, it’s really tough, and something like that would be very useful. I’m not on Bluesky enough to really make a difference, but you know, on LinkedIn, maybe even Facebook, that would be awesome. Maybe they’ll pay attention to this and follow suit. Also, beehive with the communities, I think, is terrific because building a community around a newsletter can be tough.

And I think this might signal a way that Substack and Ghost and the others might be able to play in that space. So it was all interesting, Dan, but those were the two that stood out for me.

We talk about thought leadership from time to time on FIR. It has been a tried-and-true content marketing tool for a long time.

It has also been a source of some cynicism.

A stack of research has landed over the past few months that says two things at once: Thought leadership is producing measurable financial value, and most of what organizations are publishing under the label of thought leadership is utterly worthless.

Since two things can be true at the same time, both of those things are true.

The gap between them is where the opportunity lies for those of us who do this kind of work.

Let me start with the number from Axios that got my attention in the first place.

In April, Axios reported on a study from a firm called Cardinal 40 that found high-quality CEO thought leadership was associated with an average of $367 million in shareholder value in a single week.

Here is how the researchers got to that number.

They analyzed more than 1,000 examples of CEO thought leadership from S&P 500 companies and measured each against abnormal stock returns, deliberately excluding anything tied to market-moving news or disclosures.

They were trying to isolate the effect of the words themselves.

Then they did something really interesting.

They tested more than 60 common writing traits—tone, readability, and the kinds of things we all obsess over when we are editing copy.

They found nothing that explained why some pieces outperformed.

So they used AI, because of course they did.

They compared each document with a curated canon of genuinely standout thought leadership and found that communications that sat semantically closer to that canon were associated with stronger returns.

The gap between top-tier and bottom-tier thought leadership worked out to about a nine-tenths-of-a-percentage-point swing in stock performance the following week.

For the biggest companies, that is not a rounding error.

The report estimates as much as $25 billion across the Magnificent Seven—the seven megacap U.S. technology companies: Nvidia, Apple, Alphabet, Microsoft, Amazon, Meta, and Tesla.

The research also found that more thought leadership does not produce more value.

Weak or low-quality communications correlated with neutral or negative outcomes. In the age of AI slop, volume is not merely useless. It can cost you.

Compare that with The Harris Poll’s research on the ROI of thought leadership.

Nine in 10 executives say thought leadership is critical to building authority, and only 20 percent say theirs is actually effective.

Executives in that study estimated a 14-times return on investment, and Fortune 100 executives put the annual value at about $3.6 million.

I need to hedge here a little.

The Harris fieldwork was conducted in May 2022 among 500 U.S. employees at the director level or above. It is still being cited in 2026 as though it is fresh, and it is not.

Second—and this applies across the board—nearly every organization publishing research on the value of thought leadership sells thought leadership.

Harris has a thought-leadership practice. IBM’s Institute for Business Value is a thought-leadership shop. Cardinal 40 evaluates thought leadership for a living.

That does not invalidate the work, but it should temper any enthusiasm you feel about the research.

For what it is worth, IBM’s research is the most consistent of the batch.

Eighty-eight percent of executives consume thought leadership, 87 percent say it shaped a purchase decision within the previous 90 days, and about half of C-suite leaders credit it with driving revenue growth.

One more data point from the Axios piece is something I cannot stop thinking about.

Mentions of “storytelling,” “narrative,” and “storyteller” on corporate earnings and investor calls are up 65 percent since 2020, according to AlphaSense.

The language of our discipline has migrated into the language of capital markets.

It is important to treat the dollar figures as directional rather than literal. Correlation is doing a lot of work in these studies.

Coherent, original executive communication may well be a proxy for a well-run company rather than a cause of its performance.

But the through line across all this research is consistent, and it is the one you can actually act on: Quality is doing the work, and quantity is doing damage.

If the value is real, why is only 20 percent of it working?

The Content Marketing Institute brought together a group of practitioners in July to work through exactly that question: Jill Roberson from Dataweavers, Andrea Ames from Eaton, Lindsey Hagen from Conductor, and the Content Marketing Institute’s own Robert Rose, one of my favorite people to read and listen to.

I love This Old Marketing with Robert Rose and Joe Pulizzi.

Jill Roberson made a point that stood out for me: We have to reset expectations for what thought leadership even is.

Hagen’s point was that the bar has simply risen.

You have to be useful and unique now, and the standard for what qualifies as valuable is much higher than it was.

Roberson recommended putting the hypothesis at the beginning of a thought-leadership piece and making it unmistakable, then delivering on it immediately.

If people are not getting the insight they came for, and getting it quickly, they are gone.

But delivering quickly is not the same as creating quickly.

Ames’s advice was to slow down and be genuinely intentional about the topic.

Robert Rose made the observation that I suspect a lot of you have been waiting for someone senior to say out loud: Our industry has convinced itself that speed is its foundational value, and it just isn’t.

Then there is gating.

Ames said Eaton does not require contact information for its content. There are no forms you have to fill out before you get the download link.

Her reasoning is the reasoning of 2026: She wants large language models to be able to include Eaton’s thought-leadership pieces in the results they produce.

Being exclusionary, she argues, mostly hurts you.

That means the lead-capture form—which has always been a tax on distribution—is now also a tax on being cited by the systems your buyers are querying before they ever contact you.

The Content Marketing Institute also ran a piece in the fall by Abid Rahman, written with Kate Houston, who runs executive thought leadership at Amazon Web Services.

Their diagnosis is pretty blunt.

AI can draft, polish, and structure this content with remarkable efficiency, but it cannot supply credibility, lived experience, or judgment.

It reads as though anyone could have prompted it because anyone could have prompted it.

They offer three ingredients for the real thing.

The first is credible experience.

I talk about “genuine lived experience” somewhat derisively because I read people on LinkedIn saying, “AI has no lived experience,” and then I look at the kinds of things they are writing, which required absolutely no lived experience.

But in the case of thought leadership, it really does matter.

You have to have credible experience to support your ability to make these proclamations.

You also need a genuine audience need and an insight that not many other people can provide.

Then you apply a five-step framework: Define the goal. Choose the focus. Shape between one and three core themes. Build a voice ecosystem of leaders, customers, and advocates who actually have some standing. And map the stories to the right channels.

Their measurement point is one I would like to tattoo on a few people’s foreheads: Thought leadership is not an engine for marketing-qualified leads.

In one of their programs, they do not blast out content at all. They put a CEO in credible venues.

Under those circumstances, brand awareness among the ideal customer profile rose from 17 percent to 51 percent in one year, and request-for-proposal volume increased three-and-a-half times.

Could they attribute a single article to a single lead?

Of course not.

That is the honest answer most of us should be giving.

Now, a different angle.

Yogesh Shah, writing in Entrepreneur—and this goes back to January—argues that the problem is not the thinking. It is the container.

We are in a zero-click world. Audiences do not leave the platform they are on.

Roughly 90 percent of decision-makers say they are more receptive to companies producing high-quality thought leadership, yet engagement keeps declining anyway.

His question is: If a report can be summarized in ChatGPT in seconds, why would anyone read it?

His answer is what he calls experiential thought leadership.

Turn the insight into something people are in rather than something they open.

Think of a live discussion, a workshop-style webinar, a tightly curated roundtable, or a podcast that puts listeners inside a recognizable scenario instead of offering an expert monologue.

He is emphatic that this does not require a large budget. It requires one well-designed moment in which attention is protected.

You can see the tension between these two pieces of advice.

The Content Marketing Institute says to slow down and do the deep work. Entrepreneur says the document is the wrong delivery mechanism.

I do not think those ideas conflict.

There is a line in a Savanta piece from June that I think captures the entire argument in 12 words: You can replicate a product, but you can’t copy a point of view.

The case study from the author of that piece, Matthew Mott, is aimed at technology companies, but I think it applies elsewhere.

A competitor can reverse-engineer your features, match your pricing, copy your positioning, and even hire your people.

What it cannot copy is a track record of saying interesting things that turned out to be correct.

That builds slowly, and it compounds.

His second observation is that buyers cannot really evaluate an AI product.

The technology is opaque, and every vendor’s claims sound alike. Buyers stop assessing the product and start assessing the people behind it, looking for evidence of judgment.

They are conducting that assessment before they ever talk to you.

The sales conversation does not start from zero. It starts from whatever reputation you have already built.

He also argues that relatively few companies are publishing practical, original research on AI right now.

Most of what exists is either so hedged that it is useless or so optimistic that it is not credible.

In a few years, everyone will have a program, and standing out will cost far more.

So, if you are already publishing thought leadership or planning to, what does all this mean for you?

I have a list.

Of course I have a list.

First, audit your top pieces from last quarter and apply the swap test.

If a competitor could have published the same piece with its logo on it, you did not produce thought leadership. You just cranked out content.

Second, find your proprietary data.

This is where I think communicators sell themselves short.

You have more than you think: your own operational data, customer-service logs, field observations, and the ability to conduct surveys.

Survey your employees. Survey your customers. Survey the industry.

The Content Marketing Institute’s Jasmine Williams makes the case for treating thought leadership as a platform rather than a campaign.

One flagship study becomes the hub, and articles, webinars, sales enablement, and employee advocacy become the spokes.

That is a repeatable model.

Third, put the thesis in the first 60 seconds.

Not the context. Not the setup.

Put the claim in the first 60 seconds.

Fourth, reopen the gating conversation and reframe it.

It is no longer lead capture versus reach. It is lead capture versus being cited by the machines your buyers consult first.

Segment your library.

Some assets should stay gated because a download genuinely signals buying intent. But your flagship research probably should not be among them.

Fifth, take one asset you published this year and turn it into an experience: a roundtable, a working session, or a recorded session with someone who disagrees with you.

I think we call that a debate.

Sixth, change what you are measuring—and change it before someone asks you to defend it.

Measure speaking invitations. Measure journalists citing your framework. Measure analysts referencing your numbers. Measure employees sharing the work without being asked.

Denise Brosseau of the Thought Leadership Lab calls the underlying discipline “stick-to-itiveness”: the willingness to keep showing up long enough for any of that to accumulate.

Seventh, protect the executive’s actual voice.

This is the piece only we can do.

AI is a genuinely useful accelerant. It can turn an interview into an article, sharpen the structure, and catch the flabby paragraph.

What it cannot do is have a point of view.

If your CEO’s byline reads like a competent prompt response, you put your CEO’s and your company’s credibility at risk.

Let me end this segment with a little history.

The term “thought leader” is generally credited to a fellow named Joel Kurtzman, who was editing Strategy+Business back in 1994.

He meant something specific: someone addressing the questions senior executives were actually wrestling with.

More than 30 years later, the term has become a punchline.

It became one because we industrialized it. We turned a description of rare people into a content category with a production quota.

The research that came out this year is essentially the market telling us it can still tell the difference—and that it is willing to pay for the real thing.

That is not a bad position for communicators to be in, is it?

Now for another awkward transition to my final report.

I’m going to end with something a little lighter, although there is a real point buried in it.

Knowledge at Wharton wrote up a new research study published in the Journal of Consumer Psychology titled “Effectively Communicating Uncertainty: The Persuasive Impact of Different Types of Hedges.”

You know hedges: “That could work.” “That might be a good approach.”

We all hedge.

Yet most communication training treats hedging as a bug to be trained out of us.

Jonah Berger’s research team ran seven studies and split hedging into two dimensions.

The first is likelihood.

Is your hedge low-probability—“might,” “could,” or “it feels like”—or higher-probability—“likely,” “should,” or “arguably”?

The second is perspective.

Is the hedge floating free, as in, “It sounds like”? Or is it attached to a human being, as in, “In my opinion,” or “It sounds likely to me”?

All seven studies agreed: Higher-likelihood hedges and personal-perspective hedges are more persuasive because they make the speaker seem more confident.

Berger’s example is a mechanic saying, “The repair might work,” versus, “I believe this repair will solve the problem.”

Both statements convey uncertainty, but they have a completely different effect.

The personal version means someone is taking ownership.

Berger describes this as a communication sweet spot. You get the protection of not overclaiming without paying the credibility tax.

It is important to point out that the effect weakened when the communicator was a brand rather than a person, because confidence mattered less.

That is one more argument for having actual humans deliver your message.

I went looking for research that either supports or contradicts this, and it turns out the findings land right between two camps that do not agree.

On one side are decades of work on what is called powerless language: hedges, hesitations, and tag questions.

This research suggested that hedges may be the most damaging of all the powerless markers.

Researchers found something genuinely alarming: When a topic mattered to people, powerless markers did not merely make the speaker less appealing. They flattened the arguments.

Strong arguments performed no better than weak ones once the hedges were added.

On the other side are the uncertainty-communication researchers.

Researchers at the University of Cambridge’s Winton Centre have spent years studying how to convey uncertainty in facts and numbers.

Another study involving more than 10,000 participants found that putting a numeric uncertainty range around COVID statistics slightly reduced trust in the number itself but had no effect whatsoever on trust in the source.

Being candid cost the communicator nothing.

A meta-analysis published this year finds the overall effect small and highly dependent on how uncertainty is expressed, with verbal hedges doing more damage than numbers.

Put all of this together, and here is my take: The problem was never uncertainty. It is vagueness.

Saying, “Here is what we know, here is what we do not know, and here is what would change my mind,” reads as confidence.

Mumbling, “It could go sort of either way,” reads as evasion.

It is the same actual state of knowledge, but the way it is expressed produces the opposite effect.

I would argue that this matters more for us now than it has in years, because the machines drafting our first drafts hedge constantly—and they hedge in the weak way: low likelihood, no perspective, and nobody’s name attached.

You may have noticed that Neville and I hedge our way through every episode of this podcast.

We say things like, “This is correlation, and correlation is not causation.” We say that you should treat a figure as directional.

We note, as I did just a few minutes ago, that a survey being cited is four years old.

It turns out that hedging might have been the right call.

Or let me try that again.

In my view, that was almost certainly the right call.

I would love to tell you when the next monthly episode will be, but Neville and I have not settled on that yet.

Nor do I know when he will be up for recording a short midweek episode.

I may do one solo. We’ll see how it goes. We’ll see what kind of news or research crosses the transom.

Until I get answers to all those questions, that will be a 30 for this episode of For Immediate Release.

The post FIR #523: No Brand Is An Island appeared first on FIR Podcast Network.

Podcasting 2.0 is the open-source movement launched by Adam Curry and Dave Jones to preserve and extend podcasting’s open, RSS-based ecosystem. In this episode, Shel and Neville explore the initiative’s core features — including the Podcast Index, enhanced RSS metadata, transcripts, chapters, podrolls, live notifications, and listener-supported “Value for Value” payments — while weighing its potential to reduce dependence on dominant platforms such as Spotify, Apple, Amazon, and YouTube. The discussion also addresses obstacles to adoption, including limited awareness, uneven support across hosting providers and apps, added complexity, and the need to demonstrate clear benefits to listeners. For communicators, the larger implications involve channel ownership, accessibility, content reuse, AI discoverability, resilience, and the risk of building audiences entirely on rented platforms.

Links from this episode:

• Podcasting 2.0 — Making Podcasts Better for Everyone
• What Is Podcasting 2.0? And Why Should I Care?
• Podcasting 2.0
• What Is Podcasting 2.0?
• What You Need to Know About Podcasting 2.0

The next monthly, long-form episode of FIR will drop on Monday, July 27.

We host a Communicators Zoom Chat most Thursdays at 1 p.m. ET. To obtain the credentials needed to participate, contact Shel or Neville directly, request them in our Facebook group, or email [email protected].

Special thanks to Jay Moonah for the opening and closing music.

You can find the stories from which Shel’s FIR content is selected at Shel’s Link Blog. You can catch up with both co-hosts on Neville’s blog and Shel’s blog.

Disclaimer: The opinions expressed in this podcast are Shel’s and Neville’s and do not reflect the views of their employers and/or clients.

Raw Transcript:

Neville Hobson: Hi everyone, and welcome to For Immediate Release. This is episode 522. I’m Neville Hobson

Shel Holtz: I’m Shel Holtz, and Neville, we’ve been doing this show for more than 21 years. When we started, there were maybe 400 podcasts. There was no Apple Podcasts to help people find and subscribe to shows, and every podcaster was what today they seem to be calling an indie podcaster. What’s not an indie podcaster? That would be Joe Rogan, for example, on Spotify collecting money. He’s not an indie, he’s mainstream media. So I try to follow the podcast industry. I subscribe to some newsletters. I read some people who talk about it. But somehow I only recently encountered Podcasting 2.0. This thing has been around since 2020. Despite the name, it’s not a new audio format. It’s not a new app or a replacement for RSS. It’s an open source movement launched by, guess who? Adam Curry, the podcasting pioneer, along with a developer named Dave Jones. God, there’s a lot of Dave Joneses out there. Its mission is to preserve, protect, and extend the open podcasting ecosystem. Now, that word open matters. Traditional podcasting works because creators like us publish an RSS feed that many different apps can read. Nobody has to upload a separate master copy to each player. But over time, discovery and listening have become concentrated in large corporate directories and platforms like Apple, increasingly Spotify, Amazon, and YouTube, but there are others. These companies set their own rules for their own services. Spotify’s rules explicitly say that it can remove content and suspend or terminate accounts. You can call that moderation, deplatforming, censorship. There’s no denying the underlying power these services have. Spotify can remove a podcast from its service. If the creator independently controls the RSS feed and hosting, Spotify can’t erase the podcast from the entire internet. The danger comes when creators and audiences become so dependent on one proprietary platform that removal there is effectively removal from public view. Podcasting 2.0 was designed to reduce that gatekeeper risk. Its answer isn’t that every app has to carry every show, it’s that no single app or company should be able to make a show disappear everywhere. Now, the initiative has several major pieces. The Podcast Index is an open directory that apps can use instead of depending on one company’s catalog. I checked, and FIR is listed, as are our other active shows on the FIR Podcast Network. The podcast namespace adds new backward-compatible tags to RSS feeds. Those tags can provide creator-controlled transcripts, richer chapters, information about hosts and guests, live stream notifications, alternate audio and video versions, licensing information, and a podroll of shows creators recommend. Remember blog rolls? This is podrolls. There’s also PodPing which alerts apps quickly when a feed changes, and there’s a really much-discussed thing called Value for Value. It’s a model that lets listeners support creators directly, often through tiny Bitcoin payments called sats, S-A-T-S, and attach messages known as boosts or boostagrams. And, yeah, I was listening to the Podcasting 2.0 show with Curry and Jones, and they were shouting out everybody who gave them a boost the Bitcoin element gets disproportionate attention, but it’s optional. Podcasting 2.0 is much broader than cryptocurrency. And by the way, there’s a vertical market application of Podcasting 2.0 called Godcaster. That’s a defined community of religious podcasters who have embraced Podcasting 2.0. The question is whether this model could work for, say, corporate ecosystems, universities, trade groups, nonprofits, and the like. And that explains why communicators should care or at least know about all this, because this really is a conversation about channel ownership, interoperability, accessibility, and resilience. Accurate transcripts improve access and make our content easier to search and reuse. Chapters and person tags make expertise more discoverable. Podrolls let organizations recommend trusted voices without surrendering discovery to Spotify or YouTube and their algorithms. And open distribution reduces the risk of building an audience on rented space. Now, there are caveats. Support remains uneven. I didn’t even learn about it until a couple weeks ago. Hosts like Libsyn, which hosts FIR, and podcasting apps implement different subsets of the standards. Open infrastructure doesn’t eliminate legal obligations. It doesn’t change hosting company policies. There are other choke points. And decentralization doesn’t automatically make the content accurate, ethical, or responsible. But the core idea is important, and that’s that podcasting began as an open medium, not a collection of corporate content silos. Podcasting 2.0 is an effort to modernize that open model without giving up what made podcasting distinctive in the first place. For communicators, the lesson extends well beyond audio. Distribute widely, but retain control of the source, the identity, and the relationship with the audience

Neville Hobson: Yeah, it’s quite a story, Shel, I think. Like you, I hadn’t really heard of this other than the fact I did come across Podcasting 2.0 website when Adam Curry launched it back in, what was it, 2021, 20- 2020. But since then, no, haven’t heard anything about this at all really other than some kind of, aside comments here and there on on a couple of tech podcasts. And I’m thinking what you’ve outlined or makes complete sense to me. So why hasn’t this been thought about before even? I think it has in part. I’ve read people talking about this online, particularly on making content more easily consumable as they see it and there we’re talking about an idea that’s not new. Apple’s been offering this for a while, which is chapters, splitting up your content into chapters. But that’s only Apple. It doesn’t transport, and therein lies one of the issues with this, I think. How could you put it? There are some concerns I can see. I’ll come onto the pros in a minute. But I think is this not fragmentation of something that’s going to require quite a bit of a learning curve to figure out what to do with this? I’m also thinking that, is this going to open another standards race? Open standards only work if enough people adopt them, otherwise there is becoming another well-intentioned technical layer that only enthusiasts use. We’ve seen that. But, A broader, top-level question is, are we looking at the next stage in podcasting’s evolution, or are these features primarily serving podcast creators rather than podcast listeners? In other words, who’s getting the greatest benefit? That’s what I’m wondering. And I think it, it does… The fragmentation issue I think creates complexity. Features, bolting on new features more metadata doesn’t compensate for weak storytelling, and you have to have that sorted out. And I think there’s a risk of enthusiasts becoming excited by all this, while listeners simply want worthwhile content. The interesting thing, though, a-and you pointed this out in your intro, that the where we’re at now with podcasting is the marketplace is largely controlled or dominated by big platforms. You mentioned Spotify, you mentioned Apple. If we go to look at the analytics on Libsyn as to where, how people get our content, there’s a long list of 20-plus podcast platforms. Some of them, some of them never even heard of, yet there’s, you can imagine an episode has got, six downloads on that platform and 200-and-something on another platform. So it’s like we like to say, “Listen to us wherever you get your podcasts.” So how do we introduce this into that landscape in a way that literally isn’t complexity from the fragmentation? Because it will be fragmentation. And not– And who’s not– who’s to say that Spotify and the others aren’t going to respond not in a positive way to this, ’cause this is their control slipping away. So this is what I spot as some of the issues. I think the… Another standards race is maybe- more concern one of podcasting’s great strengths has always been its relative simplicity. Wasn’t like that when we started, mind you, but that’s how it is today. This introduces another layer of standard, certification, and implementation. We’ve seen this before. Social media standards, RSS extensions, schema markup, countless proprietary platform features. So it’s not a pretty looking landscape, I would say. Plus as we are talk– We’ve talked about this ourselves, but others are talking about this. This is podcasting’s time. It’s going to play a bigger role in organizational communication, particularly as podcasts play a growing role in organizational and employee communication. So how does this all work, where you’ve suddenly got these things that sound appealing to very appealing to creators? I think probably not so much from listeners whose sense complexity is what they’d be looking at. So you’ve have to make it very easy and simple. That said, I think there are some big advantages from it. You’ve mentioned some. One that strikes me immediately, richer, more accessible content. It turns an audio file into a more complete communications asset, it seems to me. So transcripts, chapters, structured metadata makes a podcast easier, and this is a big appeal, Shel I would say. Easier to search, easier to quote, easier to repurpose, easier to reference internally, and make accessible to people who cannot or don’t want to listen to something. So you make it broader. So you could also say, many organizations already struggle to maximize the value of long-form content. These features make it much easier to reuse a single conversation across newsletters, blogs, social posts, knowledge bases, internal communication. We’re always talking about content reuse as communicators. Podcasting 2.0 makes that much easier because the structure is built into the episode itself. There’s tons more we could talk about in this vein, but I think that’s enough for now. I think there are some major cons that would worry me if I were thinking about, let’s see how we can take advantage of this. It’s got a homebrew feel about it, which isn’t a criticism by any means. That’s how podcasting started. The landscape’s way different now. I could see a big role for AI in constructing the landscape, if you like, constructing it and helping you bring this into your plans. But this again it’s big work to get this done, it seems to me.

Shel Holtz: yeah, I think the biggest challenge that Curry and Jones face with this is building awareness and support. If I’m a podcaster for 21 years and hadn’t heard of it, you heard about it when it launched and heard nothing since then there’s a serious awareness problem here. And that’s what’s going to keep this from adoption. I’m not worried about fragmentation. Podcasting started with the RSS feed. This is something that Dave Winer came up with working in hand-in-hand with Adam Curry, who developed the podcatcher that would recognize that extension that Winer created. This did not render those RSS feeds useless to the RSS newsreaders that were out there. They still got them. They just ignored that extension because they didn’t have any way of playing a media file. So they still saw it. I have to believe that an RSS feed with all the new stuff in it is still going to be an effective RSS feed. The problem is that you have the hosting services, as I mentioned, we have been hosted with Libsyn, not since the very beginning, but pretty darn close

Neville Hobson: Yeah

Shel Holtz: Right. Let me start that thought again. The problem is convenience. If you make Spotify the place you go for podcasts and they’re listening to FIR and we say something offensive and they decide to take us off they’re not going to go look for us elsewhere. They’re just going to find other podcasts because they use Spotify. If you do a deal with Spotify, and you have to be pretty good, pretty famous guarantee a lot of downloads. But if you do a deal with Spotify, that’s the only place people are going to find that podcast. And again, you do something that violates the terms of service or their standards and they take you off, then you’re off. You’re gone everywhere. So I like the idea of this standard. I would just like to see some agreement across all of the hosting platforms and the discovery platforms that we will enable all of these on our platform so that listeners get the benefit. And you articulated some of those benefits to the listener. They don’t have to know that’s courtesy of Podcasting 2.0 any more than they need to understand that there’s an extension in the RSS feed in Podcasting 1.0. They just know that this is what they get when they subscribe to a podcast. But I love the idea of they’re not having to go to the show notes on our website to get the transcript. And frankly, I like the idea of people who love the show being able to support it with a micropayment that sends a message to us. I think that enhances the listener-podcaster relationship more than just commenting on a LinkedIn post or on our website or whatever. So yeah, I think there’s a lot to, to recommend this, but I think there are lots of obstacles in the way. And as you mentioned, there are also issues that don’t get resolved because of this Yeah, and Dave Jones is a developer, so I’m sure he’s working on all of this and probably has answers to some of those questions. I think it’s largely in his and Adam Curry’s hands to get the word out about this. If I were them or if I were counseling them, I would suggest that the audience that you need to be aiming at is podcasters the creators. And the message is tell your hosting service that you want these features implemented. The more they hear this and the more they see their customers changing hosting platforms to one that does embrace all of this, the faster they’re going to adopt the standard, and this will work for everybody. But I don’t see that effort underway, and I would advise listeners if you’re curious about this, visit their Podcasting 2.0 website, but also give a listen to the Podcasting 2.0 podcast. It’s typical Adam Curry. There’s a lot of digression and a lot of talk about completely off-topic subjects. But when they do zero in on Podcasting 2.0 it’s really interesting to hear them talk about this and where it is and where it’s going.

Neville Hobson: I would say Libsyn, we’ll be in touch

Shel Holtz: You can count on it. And that’ll be a wrap for this episode of For Immediate Release

The post FIR #522: Is Podcasting 2.0 The Future of Podcasting? appeared first on FIR Podcast Network.

Your brand is no longer defined solely by what you say about yourself. Increasingly, it is defined by the answers AI gives when someone asks about you.

That simple but profound shift lies at the heart of The Answer Economy, the forthcoming book by Pete Blackshaw, entrepreneur, founder of BrandRank.ai, and former Global Head of Digital and Social Media at Nestlé.

As AI assistants and agents become increasingly influential in how people discover information, evaluate products and make decisions, organisations face a new communications challenge. It’s no longer enough to tell your story well. Your organisation also needs to be accurately understood by the AI systems that increasingly act as intermediaries between brands and the people they serve.

In this FIR Interview, Pete joins Neville Hobson and Shel Holtz to discuss why AI should be viewed less as another marketing channel and more as an auditor of organisational credibility. Together, they explore why trust, transparency and evidence are becoming more important than marketing claims, how different AI models develop different perspectives on brands, why communicators need to think beyond traditional search optimisation, and what organisations can do today to prepare for an increasingly agent-driven future.

For communicators, the implications are profound. Success in the answer economy won’t depend on producing more content. It will depend on whether an organisation has earned the evidence, transparency and trust that AI systems increasingly use to evaluate every claim it makes.

In this conversation, we discuss:

• Why Pete believes AI is becoming an auditor of organisational credibility rather than simply another information retrieval tool.
• What he means by the idea that “your brand is as strong as its answers.”
• Why evidence increasingly matters more than messaging in an AI-driven world.
• The concept of a “book of truth” and why organisations need to make trusted information easier for AI systems to understand.
• How and why ChatGPT, Claude, Gemini, Grok and other AI models can develop different perspectives on the same brand.
• Whether communicators need to understand AI “worldviews” as well as human audiences.
• Why corporate communications could become one of the most strategically important functions in the age of AI.
• How organisations should prepare for AI-generated reputation challenges and new governance responsibilities.
• What AI agents could mean for marketing, purchasing decisions and brand influence.
• Pete’s advice for communication professionals on becoming “answer ready.”

About Pete Blackshaw

Pete Blackshaw is founder and CEO of BrandRank.ai, an AI visibility and brand intelligence platform that helps organisations understand how AI answer engines evaluate brands.

A two-time technology entrepreneur, Pete previously founded PlanetFeedback, one of the earliest consumer feedback platforms, which was acquired by Nielsen, where he later served as a senior executive. He also established Procter & Gamble’s first interactive marketing team before spending nine years as Global Head of Digital and Social Media at Nestlé, leading the company’s worldwide digital transformation initiatives.

Throughout his career, Pete has focused on the intersection of consumer trust, digital communication and brand reputation. His forthcoming book, *The Answer Economy: How AI Agents Will Decide Your Brand’s Future*, published in September 2026, draws together more than two decades of experience helping organisations navigate the evolving relationship between consumers, brands and digital technology.

Resources

• Pete Blackshaw on LinkedIn
• BrandRank.ai
• The book: The Answer Economy: How AI Agents Will Decide Your Brand’s Future
• Pete’s The Answer Economy newsletter
• Search previous FIR interviews with Pete Blackshaw (2005, 2007 and 2009) on the FIR archive site.

Transcript

A transcript of this conversation follows, lightly edited for clarity and length.

Shel Holtz (00:04)
Hi everybody and welcome to a For Immediate Release interview. I’m Shel Holtz.

Neville Hobson (00:09)
And I’m Neville Hobson.

Shel Holtz (00:11)
And we are thrilled to have Pete Blackshaw back with us. Pete, this is your fourth appearance, I believe, on FIR. And it’s been a while. I think is what? It was 2009, I think, was the last time. But it’s great to have you back. I’ve been following you ever since then. Certainly read your content on LinkedIn and subscribe to your newsletter. So very happy.

Pete Blackshaw (00:21)
It has been a while.

Yeah.

Shel Holtz (00:38)
Anxious to have this conversation and the reason we reached out to bring you back on FIR interviews is because of some research that you have been doing for a couple of years that has resulted in quite a LinkedIn post and a new book coming out in September. tell us about all this and yourself.

Pete Blackshaw (00:57)
Yeah, sure. Well, I’m a native Californian who’s here in kind of adopted Cincinnati as my is my home. I have kind of had a mix of is my s you know, two time startup founder, first one I sold to Nielsen, which was in that space that you and I were talking about, you know, viral complaints and early social media. And and I’ve always been, you know, if there’s any through line across my career, I’d say it’s

The consumer meets trust meets digital. And both of the books that I’ve written kind of cover that. But in addition to being a startup founder, I’ve also worked in a large lot of the large, you know, multinational corporations, you know, many of whom I’m, you know, the types of companies I’m selling to. So I co founded P and G’s first interactive marketing team. Remember when we called it that back then? I

was a senior executive at Nielsen after I we sold my first startup to them. And then most significantly I spent nine years at in Switzerland as the global head of digital for Nestle. And ironically that kind of came in the wake of a a bit of a crisis that we all remember, you know, with Greenpeace, where they kind of recruited me in to kind of help to address all of that. And then I did a five year stint

Neville Hobson (02:18)
Ha ha.

Pete Blackshaw (02:22)
after Switzerland was recruited by P and G and Kroger and some of the Cincinnati companies to launch a startup accelerator and did a little bit of work in venture capital. But I’ve loved being back in the startup world and yeah, looking forward to the conversation.

Neville Hobson (02:39)
Terrific. So we should to kind of warm us up. I’ve got a question to start with that is a very, very simple one, actually, Pete. when I was looking into the the book that you’re publishing and looking at the content, what you’re covering and all that stuff, I saw I saw some huge kind of resonance with what we talk about in FIR. And there’s a lot of overlap, which I which I found really, really exciting because that that’ll fuel some of what we’re gonna talk about today, I think. But

Pete Blackshaw (02:45)
Yeah.

Neville Hobson (03:09)
First question, which is kind of a framing question. You’ve been talking about consumer trust and digital influence since the early social media era, if not earlier than that even. So this question this is my question. What feels genuinely different about this AI moment compared with previous platform shifts?

Pete Blackshaw (03:29)
Yeah, it’s a great question. I think what’s fundamentally different this time is

Is accountability. You know, I often say that, you know, the big aha for me when I quit my last job to launch brand rank, my current startup, is that I was shortly after Chat GBT came out, kids were asleep, we were skiing, and I was just doing what I typically do, what I’m sure you guys do all the time, just exercising my curiosity. And then typing in things into ChatGBT like, can Nestle be trusted? Are Pampers diapers really sustainable?

And it dawned on me within seconds that this medium that is evolving is the world’s greatest BS detector. And and we started to see some of the platforms are really on the extreme side of that, like anthropic cloud, where you just can’t throw spinner slogans at them. They just kind of cut through it. And that was like the big unlock for me. It’s like, my gosh, this is not only gonna become a new purchase funnel.

This is going to become really tricky terrain for marketers that are used to controlling the message, managing the spin, maybe getting away with overflated claims. And and I was like, my gosh, I gotta measure this. Someone’s gonna have to create like a Nielsen ratings of what these answer engines say. And I really wanted to focus. I know there’s a lot of players that are out there doing.

you know, AEO or GEO, but I really wanted to focus on the hard issues, like, my gosh, are brands going to be held more accountable for sustainability? Are these very sophisticated LLMs going to just digest an entire supply chain and either say thumbs up or thumbs down? Are, you know, and and maybe and and maybe, just maybe, will brands finally be forced to do some of the things that you all three of us have been talking about across the four sessions.

Which is, are they finally gonna kind of start responding to feedback? Are they gonna start inviting questions? Are they gonna start acting more with empathy? Because remember, digital started there. Digital started, we called it interactive. And the whole promise was like, we’re gonna be able to answer questions for consumers. They’re gonna come to us. And I remember when I started interactive marketing at PNG, that was like the North Star. And then we kind of moved into targeted advertising at scale.

We got very programmatic, we got digital, we kind of forgot about the consumer in control. And now I think that’s really waking up. However, one of the things I say in my book is

Listen, we totally messed up search two point And I’ve talked to the folks that wrote books about that, like John Battel, or like, my gosh, that quickly became a tragedy of the commons. Nobody could tell the difference between organic and paid and and even when it moved to mobile. And we as an industry are gonna have to decide like, do we want to preserve this incredible gift to consumers? And the things that are good for consumers are also really good for business, where they’re getting, you know.

reliable, trusted, you know, answers that are just solving like everything for them. Or do we want to pollute the commons by moving too aggressively the paid advertising? Do we want to dance in the gray zone? And so the book is kind of a the answer economy is this true shift and we have got to get in front of it.

To make sure that it is nurtured in the right way. And the timing couldn’t have been better because just last week, you know, all the folks from OpenAI are running all over cons trying to grab ad dollars. And that’s that’s good. You need, you know, you need an advertising model, but marketers have a historic tendency of dancing in the gray zone. And I just think we need to really get in front of it. And that’s like the heart and soul of the answer economy. We are in a world where the brands that actually answer the questions win. It’s such a basic

pre-digital concept that now is kind of getting extra life. Brands that tell the truth win. Why? Because the answer engines kind of call your BS. you know, so so that’s kind of the heart of what I’m getting into. And I just think it’s a really important conversation. And I’m hoping that it dusts off some of these conversations that we had in the past that maybe just were too damn early.

Shel Holtz (08:06)
Yeah, I remember those days, what, around 2004, when everybody was talking about how we were now going to have brands and consumers engaged in conversation and this was going to change everything and really didn’t. But Pete, you outlined this prescription of making everything sourced, timestamped, structured, LLM findable. that’s good hygiene for sure. but you’re describing how to feed the model, the inputs it

reward. So if a brand does this well enough, hasn’t it just learned to pass Claude rather than actually be trustworthy? I mean, how how would how would Claude or or you tell the difference between a brand with real substance and a brand with just a really great brand book of truth?

Pete Blackshaw (08:50)
Yeah, well, I think a lot of that goes hand in hand if you do it right. And again, you know, there’s a difference between a verified, trustworthy book of truth and marketing. I mean, they’re not the same thing. And so what I’ve learned, you know, I’ve I’ve been at this for two years, have worked with about 80 of the world’s top brands, big brands that you know that really, you know, have really challenging issues.

In fact, the whole business model started on sustainability, you know, Nestle Canada. And I they kind of invited me in for Earth Day. And we really took a hard look at, okay, will Nestle be rewarded or punished? And the good news is that they were severely rewarded. But there are ways where you need to market. I and maybe not the word market is the wrong term. You need to make your the good work that you’re doing.

Discoverable. So for example, I have found that a lot of the companies that I’ve worked with are getting lower sustainability scores than they deserve. You know, if you look at their science and their commitments, it’s actually pretty damn good. However, they’re so backwards on digital strategy that they put all of their science in PDFs, which LLMs can’t read. And we call that content liquidity. So there’s it’s not about manipulation. It’s a lot of it is like about getting the credit that you’re due. Now, I say that.

I don’t want to sound naive with that because I realize there’s a whole industry that’s mushrooming around me that’s all about manipulation and gaming and whatever it takes to kind of get credit you probably don’t deserve. I’m not playing that game. I think there is so much upside for companies that are actually already doing good things, have products that actually work, have credible supply chains, treat their employees well, that aren’t getting the credit they deserve. And I like those.

Challenges and we’ve been able to significantly move the needle with a lot of big companies just by making sure that they load up their FAQs with their sustainability commitments that are already verified by third parties or by these LLMs are very biased towards trust signals. And so we’ve always known that quality seals, BBB, you know, fair trade,

Good housekeeping, those have always mattered, but they’re really important to the LLMs. Because if you think about what’s happening right now,

They’re in a arms race to be the single source of truth. And so they are very, very biased towards trust signals. There’s a lot of misinformation out in the marketplace that everybody goes to Reddit first. That’s not true at all. They go to the brand websites first because they know those are places where content is typically vetted, reviewed by lawyers. Brands kind of are close to their stuff and they look at that. And then if they don’t have what they want, then they’ll go to other sources.

So what marketers do, what we do is we focus on three simple metrics. And I try to, yeah, I think a lot of us in the industry are just throwing too much vernacular, too many metrics. And I try to keep it really simple. Visibility. Are you visible? So what’s the best podcast show that has to do with, you know, you know, public relations or crisis? I suspect you would probably show up. If not, then I may become your digital coach to make sure you do.

Neville Hobson (12:14)
Yeah.

Pete Blackshaw (12:15)
You know, vulnerability is the second one, which is how do you show up? And it’s different than sentiment because I often say the visibility gets you seen, vulnerability gets you remembered. And I think companies underestimate the degree to which you can be visible, but in a very negative context. And a good pre-AI example is that when I was running digital at Nestle, Wikipedia was a big pain in the butt because you type in

Nestle into Wikipedia and like 40% of the entry had to do with the company’s history with activist. And so it was like the gift that kept on punishing all the time. And so you know, A and and AI kind of compounds that it’s almost like you can’t. so that gets into misinformation, hallucination, and then what I call brand alignment, which is do the LLMs fundamentally agree with the promise that you’re putting out there on your website, your Amazon page, your TV ads?

And this is very, very humbling. Sometimes executives throw chairs at me, but that’s where the big unlock takes place. And the third area is readiness. Do you head out and market to algorithms? and then we focus on three buckets. You know, availability, do you even have available content that algorithms can read? clarity, do you speak in a consumer language? And right now, at least, they’re very biased towards conversational vernacular, which I think is good. And then the third one is depth, where

You have to have substance, the third party seals, the the validation. And so I think right now the criteria they’re using is good for the consumer, because I think it means a consumer’s more likely to get a good and a trusted response. And I think for the good actors out there that actually really that don’t BS and actually live up to their claims, I think they’re benefiting as well. but it’s gonna be very tricky environment where you’re gonna have lot of bad actors that don’t deserve to be at the top. They’re gonna

fight the bloody hell to get to the top. And there’s going to be a million vendors out there kind of say, we will get you to the top. And so it’ll be interesting. But that’s why I think we have to really think about like what this is our this is our moment right now. Like what type of digital space do we want? We messed up the previous ones. We’re 25 years into us. We still are like deluged with spam. My entire phone is loaded with artificial voices pitching me on stuff. None of them are real. And

So now we’ve got this chance to like really nurture something special. Can we do it? I don’t know.

Neville Hobson (14:42)
It’s good one. It’s a good one. Pete, one thing that really struck me is how you describe AI as an auditor rather than simply an information retrieval system. So you say, for instance, AI answer engines are now the auditors of brand credibility. We’ve talked a lot on FIR about organizations needing a human in the loop for AI. But and indeed, there are examples that are large, highly visible, very prominent of organizations who’ve really screwed up on that area.

by not having a human in the loop. But what you’re suggesting, I think, is almost the reverse. AI is now putting organizations themselves in the loop, constantly evaluating whether their behavior matches their claims. Is that how you see it?

Pete Blackshaw (15:28)
Yeah, no, it no exactly. I think the and I think there’s a number of different yeah, so what we’ll do, it’s it’s my favorite part of the model. It’s a little bit evil, but but it really is crazy insightful to clients. So we’ll take your brand promise, and every company has one, and then we’ll take like the top 10 comp claims. Oftentimes the things that you you’re sending out to the marketplace or the analyst, and we will kind of have each of the LLMs interrogate.

those claims. And then we’ll come up with scores one to ten. And it’s absolutely fascinating. And this is the ultimate unlock in understanding how the algorithm thinks. Like, you know, and and again in the book I get into all these different segments, like how does Claude think? How does Grot think? I mean, you know, right now at least, Claude is like the student radical who just is like doesn’t believe the man is like

y they’re just not gonna believe marketing whatsoever. And so I did a brand alignment test on our dashboard with Amazon. I’ve got a dashboard with Amazon. I can send it to you afterwards where I had Amazon has this statement like Earth’s most consumer centric company and then you know blah blah blah. And then I had the LLMs interrogate it and you know who gave it the lowest score? It was Claude. Claude gave it like a four out of ten.

Shel Holtz (16:47)
Claude?

Pete Blackshaw (16:51)
And then they got into all these specifics about why they simply don’t measure up. Now, the irony and the beauty of that is that, you know, Amazon is a huge partner with Claude. In fact, Claude is what undergirds Rufus or Alexa for shopping. I think Amazon’s even put some money into Claude. But, you know, this is like the beautiful irony of these, of these crazy systems. They’re kind of holding everyone accountable. And I’m like,

And what I’ve been telling brands lately is that, you know, you got to be really careful before you spend a ton of money on paid advertising, where, you know, people are just one question away from calling your BS. and then the other thing that I think is getting really tricky, and you’ll love this. One of the things that I’ve been doing lately is really telling.

Corporate communications teams, CEOs, boardrooms design for Clyde, because this is one platform that continues to grow and influence.

They act like a college radical and they are absolutely loved for better or worse by journalists, NGOs, determined detractors, yeah, financial analysts. And so I always say, like, if you can pass the Claude test, you’re probably in a good place. And I’ve actually done briefings with clients before earnings calls where I’ve literally looked at the data from like Claude, where they’re just like, no, we don’t believe it. We don’t believe it.

And they’ve almost become practice fodder to kind of figure out how do you really but the point is that yeah, we’re in this tricky environment where you got to be really accountable for what you say because these very, very smart algorithms are like, no, no, no, no, no, no, no. I don’t necessarily agree with you. And marketers have never lived with that type of accountability. I mean, it’s like Spin City, and I’m I’ve been part of that. And so I do think, yeah, the marketers that really have superior products can back their claims.

But they’re also gonna have to think about all these other areas that are gonna creep into the algorithmic judgment. Like I do think you talked about human in a loop, and you had a lot of CEOs. You know, you have Mark Pritchard was talking about that at Khan. I mean, I think everyone’s gonna be talking that, but these algorithms will kind of know whether you’ve completely sold everybody out to AI or whether you’ve kind of kept a blend. And I think some purchase behavior is gonna be based on that.

I mean, I could I could see I could see frustrated teenagers that are like already skeptical about AI creating shopping tools that say, I’m only gonna buy from companies that don’t go go too far on AI. It’s not difficult to hack, you know, on on one of the vibe coding tools.

Shel Holtz (19:32)
Pete, you out you outlined the the concept of a brand book of truth, mentioned that a few minutes ago, and I’d I’d I’d like you to sort of articulate what that is. But if every brand builds one and f and floods the zone with sourced timestamped LLM findable proof, does does Claude’s discernment survive that or do you end up in an arms race where the brands with the biggest content budgets win again? And

Pete Blackshaw (19:56)
I did.

Shel Holtz (20:01)
That’s the dynamic that that you’re saying is dead.

Pete Blackshaw (20:05)
Yeah, I do. I think a lot of the listen, I think some of the LLMs will submit to the chaos that you described. But I do think yeah, I think I think these, you know, it’s interesting because Claude is not as dependent on a paid ad model or getting all their money from subscriptions. So I think the ones that’ll get really trickier are are open AI and some of the other, you know, Google’s already a little bit fuzzy.

but they’re still, you know, wowing consumers with, you know, you know, AI overviews. But yeah, they’re just gonna have to be really careful about how they they blend. But I think it’s, you know, it’s a fair point. But I do think that you know, when I talk about book of truth, it’s not just the marketing slogans, it’s like how the product’s made. It is literally, is it truly superior and can you verify that?

You know, yeah, how do you stack up versus competition? Who are the people behind the brand? What’s the supply chain behind the brand? They’re kind of looking for all those different ingredients, even even for the purpose of like Amazon. I mean, this stuff is so real. I just put out a note to my clients this morning. I put a little blurb on LinkedIn as well, but

Amazon Prime Day was really insightful. I didn’t go, I couldn’t, I didn’t go to con last year, but I did stay glued for four days straight on Prime Day. And it was probably the biggest conversational boost we’ve seen in the history of commerce. Almost every single, you know, now it’s like every product you look at is surrounded by questions. I mean, what the hell’s going on? And then a lot of the you know, I’ve saw a lot of advertising trying to work into that. But on that platform, you can go in there and say, is this product sustainable or should I buy sustainable products?

Or should I I mean in and it’ll really give you very, very deep perspective before they start shoving products your way. And that is an absolute game changer. And so and I do think like the smart retailers will want to make sure that that the consumer kind of gets what they need. So so I may be, you know, long way of saying I’m optimistic. Where where it can get scary, you know, is if where everything got out of whack.

before was it Google was a monopoly and they had like 90% market share screw they can do whatever they want. I do think because you’ve got genuine competition, there is this real effort to like provide maximum value to the consumer. And that’s why I say we’re in a moment. You know, the answer economy is a moment. Either we’re gonna screw it up like we did before, or we’re gonna kind of turn it into a true win-win for consumers and business alike. But it’ll take some work to do that right.

Neville Hobson (22:53)
Interesting that is. I’ve been thinking when I listen to what you’re saying, Pete, a question I need to I I’m really curious about this because it I’ve been asking myself this question as I try to figure out where we’re at with all of this. What do you think? Could two different AI models, whether it’s Claude and ChatGPT or any any two, develop materially different views of the same company, the same brand?

What will that look like, do you think?

Pete Blackshaw (23:23)
it I I do this every day for clients. I we literally kind of give them we filter them through all the major LLMs, you know, from ChatGBT to Deep Seat to Perplexity and Grok. They all have different personalities. It’s no different than going after influencers, right? And influencers kind of, you know, they beat to different drummers. And so and and again, I would say Claude is the extreme librarian. They just don’t like marketing BS. They kind of just focus on the facts.

The credentialing, the science. you know, Grok is almost like hard to predict. And they do lean on a lot of the former tweets that kind of fall into it. but they are a little bit, they’re definitely they almost like personify not the politics of Elon Musk, but definitely like the almost like the unpredictable side of him and what you see. It’s like a different personality.

Gemini still, you know, you know, it’s it’s you know, the the it depends on if you’re looking at Gemini AI overviews. I mean, they all have different thinking processes in terms of the way they synthesize data, but absolutely, and I would say the new, you know, just in the same way that like a PR term might you might say we gotta we’ve gotta figure out how to break through the New York Times, the Financial Times.

And so and so you gotta think the same way. It’s like they they they think differently, they source differently. And so this is I spent the whole weekend doing this fascinating source analysis where I looked at, you know, tens of thousands of prompts and then I analyzed the sources and they have different favorites. And just recently the New York Times is finally starting to to creep into open AI, which does start to impact the character of their output.

You know, Claude tends to look a little bit more seriously at consumer reports than Joe’s review site. And so you have to know this. I mean, this is like the new PR. This is like the new influencer management. If you do not know how these LLMs think, if you don’t know what their brand archetype is, if you don’t know what they eat for breakfast from a content perspective, you’re not on top of what your client needs, in my view.

Shel Holtz (25:42)
I have a follow up to that question. Does does does this mean a brand needs to have a message strategy for every LLM or is there a through line that satisfies them all?

Pete Blackshaw (25:44)
Yeah.

Know if they have to have different messages, but they need to be very attentive to how they are filtered. I do think all the LLMs, like for example, in my analysis this weekend, they all pay a lot of attention to your brand website. Far more than I think the media has let on. And I know because I’ve just run like a million audits and I see this all the time. And so

Brands have a lot of leverage in influencing the story, especially when there’s bad information out there and the brand website or the own media is in a position to kind of correct the record. And we’ve done some really interesting work around crisis or recalls where some brands have been able to actually train the LLMs within 12, 24 hours based on getting that right information in there. But but yeah, I mean you’ve got

So I don’t think brands need to overcustomized. I think they need to be very, you know. I mean, if I were, you know, if I were heading corporate communications today, I would probably say, yeah, there’s some that I would focus on the ones that are most critical. You know, and the the ones that are most critical often have also tend to be the most loved by other influencers.

that we care about, like journalists and NGOs and the like. And so, so that’s where I would kind of put the focus on in that. Now, now that said, they’re all going to be introducing, with the exception of Claude, advertising models. And so those will be micro opportunities to influence. And we saw, you know, a lot of that, you know, OpenAI is already doing a lot of that. And there’s gonna be, you’re gonna have they’re gonna have to study like, you know,

Is it appropriate to advertise? I do have a strong point of view there that if you have high vulnerability, you shouldn’t advertise. If you have low vulnerability but low visibility, I’d say, yeah, spend all the money you want on advertising. But brands are gonna have to be really sensitive about they’re gonna have to learn the art of not making things worse. And I don’t think brands, I mean, again, going back to the conversations that we’ve had for 20 years, brands don’t know how to manage conversations. I mean, they’re like, I mean, they’re like.

Most brands are maybe are barely there on like the first question. But in the answer economy, I have this term that I use in the book called ask through, not click-through. Click through is like if I can just get that one click. You and I know we’re we’re using these tools all the time. It’s a sequence of questions. You go in there with a health query, and it’s like multiple. And every single additional question that’s satisfied that gets you further down the sail.

Or further down the path of happiness. And like brands don’t know how to do that at all. and so, but the the second you submit to these ad models where you’re sitting right in the middle of the prompt, you almost have to figure that you always have to know that stuff. So this is gonna be really tricky. It’s not gonna be one of those push a button kind of get media. You know, there’s gonna be a whole accountability that comes with it when you’re kind of in the answer stream.

Neville Hobson (29:05)
Hmm. Let’s I let me talk go back to I I guess something we discussed just a short while ago. In fact, Shel’s question about should brands ever tailor themselves differently for different models, which I if I understood you right, Pete, you basically say that’s ultimately a dead end, not really what what what they should be doing. So I’m thinking you mentioned Claude hates marketing BS or corporate spin or whatever whatever it might be.

and you describe the models like Claude or like Grok, etc., almost as having editorial personalities or or value systems. But that’s fascinating, I think, because I’ve sometimes questioned that myself, because organizations, brand managers have spent years trying to create one consistent narrative about their brand or or their organization. So I think

The question I had originally was worded are we, in other words of question. I think it’s more like we are as opposed to are we, which is entering a world where communicators have to understand not just audiences, but different AI worldviews. And I think it’s it it is interesting. my experience in this is not deliberate trying to get an answer to this, but I use myself usually a mixture between Claude and Chat GPT. So I I alternate between the two.

Claude is more rounded and rich because I fed it with so much information about who I am, a lot more than ChatGPT has. That I I I’m okay with I’m literally asking vague questions a lot of the time, and it never disappoints my experience so far. Chat GPT needs a little bit more nurturing in that regard, although it does surprise me at times with the depth of answers I get to some things when I’m doing research. So I guess I I

confuse myself even because I have no idea what the answer to this is. But I think it is something communicators should think about. Those who haven’t settled on one, you know, notwithstanding the topic Shawn and I’ve talked about recently where, you know, shadow AI is is growing like crazy in companies as people use their own thing, ignore what the what the company says. So it what what would you what would your advice be to communicators in this earth? Yeah.

Pete Blackshaw (31:25)
No, it this is the new this is the new you’re knowing it. I mean, this is the new influencer

marketing, right? That’s always been at the core of like issues management and communication and and you know, you have to know your influencer, you have to know their hot buttons, you have to know their biases, you gotta know you know, how they evolve and there is a lot of evolution and and again this is where I think we may find a year from now that hey, you know.

They’re patty cakes with brands because they want the ad dollars. Who knows? I don’t know. But but yeah, and so and brands need to think this through. And I didn’t want you to think you made the comment about dead end. I I obsess with the nuances of the platforms, but I’m not convinced brands need to over tailor the message to different…

I again I think there’s a few where they gotta be really careful about the BS factor, like anthropic, where it’s just they just gotta make sure that their claims can hold water with these judges and these filters that are processing their their information. And I think I really think brands are just they’re not ready. In fact, what I’ve concluded is that across all the major, you know, Fortune 1000 companies, they’re only like 20% AI ready.

I mean, the most obvious thing is, you know, and sometimes companies get, you know, annoyed with me. And I have been doing this all the way back from my plan of feedback days, but like most companies cannot answer questions. I mean, you can go go to your after this podcast, go to your favorite brands and like type in a really basic question, like, how do I use the product? What’s in the product? Is it sustainable? But 90% of the time they’re gonna slap you in the face with a pop-up ad. They’re not gonna, they’re either gonna fire a blank.

Or they’re gonna answer something completely differently. Like brands don’t know how to do this. In the last 25 years of digital, the most basic human need of interactivity, I want to question brands can’t do it, including the big ones. They get all the awards and spend all the money. It’s crazy. And there’s a lot of people on the inside that are like, hey, that doesn’t matter, that doesn’t pay out. Or consumer services was always considered a non-strategic call cost center.

But again, I’m sort of saying the answer economy, that’s the new purchase funnel. Like this is the new skill that we need to learn. So it’s not only how to influence the algorithms, it’s almost like how do we fundamentally change our mindset where we’re more receivers of intent. And then we have to use that as the new engagement. You know, to some extent, when someone casts Amazon’s CEO had a great quote that everybody in marketing should put on their forehead, where he basically said it was so beautifully simple.

Neville Hobson (33:59)
Mm-hmm.

Pete Blackshaw (34:12)
He was doing an earnings call and he’s talking about the progress of Amazon Rufus, which I think at that time was already generating like $10 billion in incremental sales. And he said, Hey, it’s pretty simple. Every consumer that asks one question is 60% more likely to buy. And this is almost like the North Star that brands have always been looking for in terms of engagement, right? A click half the time you’re trying to get rid of the brand, right? So get out of my face. A question is like a big lean in.

Where if you can’t convert that. And so I think brands need to understand that, like, you know, inviting the consumer to ask a question, making the website more receptive to questions, not only wins with the consumer, but it builds your database to feed LLMs. You know, because where brands are underrepresented in all the LLMs, if they that book of truth is partly an inventory issue. It’s like you have to have enough.

Scenarios, you know, how to use the product, what’s it made of, blah, blah, blah, to even start to market the algorithms. And brands don’t do that. They you’re lucky if you see maybe 20 FAQs. And of course, brands could be problem solvers for like a million things if you do it right. Tech companies are very good. So I’m I I want to be careful here. Tech companies, I think, are very good. Apple has a fantastic and have for many years, pre-AI, have just

Bent over backwards to make content available when you have a challenge. And that’s why almost every app Apple question you ask through an LLM is like pretty much right. Same thing with Microsoft. I think tech companies have always been good at having a lot of FAQs and knowledge. Bigger brands that spend the big bucks on the Super Bowl are really, really, I gotta be careful what I say, have opportunities.

Shel Holtz (36:08)
Yeah.

Pete, in in chapter nine, see, I I actually went through the book, y you argue that the next big comms crisis isn’t going to be a social media firestorm, but an AI generated answer, a brand can’t correct. because the infrastructure for rebuttal was never built. This is really interesting. I was just on a panel in Covington, Kentucky, by the way. If I’d known you were in Cincinnati, I’d have given you a call. where

Pete Blackshaw (36:33)
no way.

Shel Holtz (36:37)
We talked about pre bunking as a way to address crises, that you’ve all got all this content out there already. but y you’re saying the crisis is going to come because they haven’t done this. The con the content isn’t there to rebut what the the LLM is is saying. Can you walk me through what that crisis actually looks like and why the old crisis playbook is not gonna be effective in these circumstances?

Pete Blackshaw (36:55)
Yeah.

One of the big issues that I’ve had with a lot of our top clients is about kind of crisis and governance, which is that

You know, winning with answers is a governance issue. And it’s a big reason why I’m been really hesitant to

you know, suggests that this is all about SEO 2.0 or this is something that the search manager deals with. I mean, and you know, if your brand is as strong as your answers, a lot of people are implicated. And I think where companies really struggle in crisis is figuring out who owns it and who’s accountable.

And I do think, you know, I do make a pretty strong pitch in the book that brands have really got need to get in front of this. And, you know, there is a there’s an accountability. Like the they’re they’re bullshit detectors, who’s accountable? they’re kind of saying your products aren’t made the way you claim. Who’s accountable? there’s there’s all sorts of legal liability issues, and I think we are just in the very early stages. At some point you’ll need to interview my

My co-founder Hank Hudipol, who’s doing some really breakthrough breakthrough work around hallucination and accuracy. But you’ve got states that are now filing laws that if if the answer comes out wrong, even through an LLM, you are liable. Think about that in the health zone, right? And so so who so who is responsible? Is that the marketing team? Is that so there’s a you know, I think brands need to start thinking now, and I’m having a lot of leadership meetings and summits on this topic, they’ve really got to figure out the governance area here. And, you know, and it’s one reason why we’re trying to keep the metrics relatively simple so they really have a clear eye into what’s going on. It’s a big reason why we put almost I’d say vulnerabilities is kind of at the top of the list. But let me tell you what you get if you have governance. So without naming names, yeah, we work with some brands that have had

Very, very severe crisis issues where misinformation is even from the government is kind of stirring up the pot in terms of, you know, how the answer engines. And you’ve just you’ve got to get RD to the table, you gotta get legal compliance, marketing, even the CEO, you know, they need to kind of play a critical role. And the good news is there is I’ve done a lot of boardroom discussions and

There’s a lot of heightened sensitivity when a CEO says, My daughter just typed in this and they say we’re this. And they’re like, Why the hell is that? And who’s responsible? So But yeah, these these issues are really, really tricky, and a lot of stakeholders need to come together. And and that is and I think it’ll probably be a little bit blurry in terms of who owns it. Like right now, brands have these AI

Heads of AI. I don’t know if those jobs will last very long. Sometimes you know are they gatekeepers, are they enablers? Are they just, you know, I mean AI is now kind of part of everything. So I think who owns what will be a bit fluid for the coming years.

Neville Hobson (40:17)
Yeah, that’s that’s really good. I think it is. Yep. So it actually interesting Pete what you’re saying, listening listening to how you describe it it amazes me how some companies just are so off the trail with with a lot of what they need not to be in that position. They need to to truly pay attention to where this is all going. And we’ve mentioned this in a number of episodes where we could

Pete Blackshaw (40:24)
That helpful?

Neville Hobson (40:51)
you know, share many examples of where we see instances where that is simply not happening. so let’s talk about AI agents. Yeah. Mm.

Pete Blackshaw (40:58)
But but in fair but in fairness, in fairness.

Let’s just put this in perspective. We’re still only what a little over three years into this. I mean, we’re up to like five billion prompts a day, and this stuff started three years ago. So yeah, companies are always gonna be slow. But the good news with this, I do feel like

There’s a feeling of a sense of urgency. Like there it’s it’s a bit of an shit moment. Like we’ve got to figure this out. And so and then, you know, how do you, you know, how do you really capitalize on this? And even it’s funny, like launching a startup, the one thing you dread is like, my gosh, it’s gonna take forever to get to get a vendor number. And we’ve had some companies that typically take like three years to get a little small startup in Cincinnati a vendor number to literally three weeks. So I do think there’s

There’s a memo, there’s a bell that’s ringing inside the organization. It’s like, shit, the purchase funnel has changed. we are really accountable. Every stock analyst is now digging up dirt on us. Or good news, through these tools, we’ve got to act. Then they’re like, Well, who owns this? Is it wait? It’s digital, right? No, well, wait, maybe it’s RD because they’ve got the most substance, you know, to kind of put to the table, but we don’t really think about them as marketing.

Neville Hobson (41:55)
Mm mm.

Pete Blackshaw (42:22)
Or may is it sales? You know, it’s just like it’s a bit of a cluster right now, but it’s a good conversation. Companies really haven’t had this discussion in earnest for a long time. I think digital is a little is like conveniently tucked into marketing. And now you’ve got a whole different world order that companies need to think through. And it’s gonna be a really big test for like CEOs out there. Who gets it? Who you know, CEOs are gonna play a critical role in orchestrating this stuff. And

And, you know, we’ve been working with a few companies that I won’t name where the CEOs have made a massive difference and in kind of leading, you know, organizations where nobody’s really accountable for doing it to like getting organized around it.

Neville Hobson (43:08)
Yeah. I’d love to hear more stories of people, you know, organizations who really are on the ball with all this because I’m getting tired of hearing all the stories about these companies who are not. They’ve the not that they’ve dropped the ball, they haven’t even grasped the ball yet. In fact, Shel and I’ve talked on a couple of episodes, two conflicting surveys. One about how CEOs are are really coming to the fore and taking control of developing AI rollouts in their in their companies.

and are providing leadership and are doing all these things. Then another survey has completely conflicting information to them. So I mean you just gotta go visit LinkedIn and you’ll see conflicts all over the place, including everyone’s got an e book they want to sell you. That’s that’s the kind of magic, magic bullet handbook.

Pete Blackshaw (43:52)
It depends on how you

classify it. Yeah, I’ve I’ve read all those studies too and you know, and and my view is like a lot of this is it’s is it an AI strategy or it’s something you should have been doing a while ago? So I posted something last week, you know, and you know, almost as a little bit of a counterpoint to the con lions, because I was kind of like, why don’t they ever give love or rewards or recognition to brands that just answer the boring question?

Neville Hobson (44:05)
Right, right.

Pete Blackshaw (44:22)
Right. At some point we’re just gonna say, God, that brand really went out of went out of their way. We should have a recognition. So I just created what I called, you know, the answer cans. And so and I started like and and I and I cited some of the companies that I wrote about in the book that and I don’t even think they use the word AI. Like, yeah, w what do you think is one of the most the best index companies on the web right now in in AI that just shows up consistently.

Neville Hobson (44:34)
Yeah.

Pete Blackshaw (44:49)
Well, I’ll give you a little hint. So if you ask anything related to like sustainability, like what company shows up first?

It’s like Patagonia. They’re everywhere. They’re everywhere. Now, I don’t, I doubt they even use the word AI there. You know, but they have been absolutely committed to driving radical transparency in their products, flooding their content with meaningful content. and they have been training the LLMs for years. Sephora, a brand in beauty that’s always been very

Neville Hobson (44:59)
Okay.

Pete Blackshaw (45:26)
Come to the calendar and I will answer you questions. I think that that model lives in the way they approach digital as well. They are severely rewarded by the LLMs. I mentioned a few of the the the I mentioned a few of the tech companies that do that particularly well. A lot of young companies that don’t have big bucks for advertising, they are very intuitive about.

Everybody that goes on my website could be my last customer. So let’s just give them the love of knowledge, of guidance, whatever they want. They are being disproportionately benefited. In fact, one of the things that I have found is that and I work with a lot of big companies that own massive budget. I’ve consistently found that, you know, for big companies, market share under indexes, over, you know, over indexes answer share.

Which means that the younger companies are actually they’re kind of winning on answer share, partly just because they’re it’s not like that they’re trying to spike the system. They’re just wired to answering questions. And so this is where the the the thesis of the book is really simple. I’m almost trying to say this without all the buzzwords and the tech gobbledygook. It’s sort of like if you treat the consumer, you know, if you kind of

Create a bit of a Wikipedia to kind of help the consumer answer every question, you will win big time in the AI world. I have seen that correlation left and right. Instead, most brands make it really complicated. We need an AI strategy. We need an AI strategy for the AI strategy we need. They create all these damn layers. And then you go to their website and they still can’t answer a question. And so this is why it’s almost like forcing the question. It’s like, you know.

The answer economy, not the AI world, the answer economy. And so we’ll see if I’m successful or not.

Shel Holtz (47:24)
All of this when I picture somebody actually doing the things that you talk about, not not from the brand perspective, but from the consumers perspective, I see them going to a chatbot and and entering a question. Sam Altman has been laser focused on the transition from conversational assistance, the chat bots, toward autonomous workflow executing agents. and he says this is a shift you’re going to see.

in the front end of Chat GPT. God knows I spend as much time in Claude Cowork as I as I spend in Claude. what is this shift toward agents, assuming all of the LLMs move in this direction, what does that do to this whole concept?

Pete Blackshaw (48:12)
Yeah, listen, I mean, I write about it a lot in the book and you know, the the tet the subtitle is, you know, how AI agents will decide your brand’s future. yeah, so a lot’s gonna be delegated, but I don’t think it’s gonna I I think there’s a little bit of overhyping that consumers are gonna completely like delegate everything to agencies. I’m not. And and I frankly, I enjoy, you know, the ask through of asking health questions. It’s sort of like, you know, and so I don’t, you know, there are gonna be certain areas where we’re gonna be totally comfortable with like

Delegating the agents, or there are other areas where we’re just gonna wanna be more in control of it. And so, but I don’t think what I’ve said earlier.

impacts any of that. I would say that i in an agentic world, brands still need to catalog their truth and make it marketable and make it visible. And and and you could almost argue that it’s going to be more important to get your act together on marketing the algorithms. Cause here’s one of the things that’s going to be really, really tricky for brands, especially in like these industries that I’ve worked in, like consumer goods and

Food is the algorithms have a very strong bias towards store brands and private label. Now it’s not because they’re tilting the scale in their favor. It’s just that in an agentic world, think about what consumers are going to do. They’re almost going to be brand agnostic. And they say, give me good product at a good price for my family of four, right?

And they’re they might even set a spec, like it’s gotta have X percent product performance. And then the algorithms are gonna do their homework and they’re come back and they say Kirkland. And then they’re gonna be saying Kirkland, Walmart equate. Because you’re gonna find that these store brands where where the and retailers are getting really good at volunteering what their products do, even their green scores, where you know, if you if we overdelegate to agents, I do think brands are in for a really rude awakening that a lot of the

Neville Hobson (49:54)
Mm-hmm.

Pete Blackshaw (50:13)
Grocery lists are full of private label. you know, where it may be the Kirkland product may be 90% of the product superiority of the comparable brand, but at like half the price. And so this is where, you know, so brands, so what brands are gonna have to do, whether they’re preparing for tough questions from consumers like us, or preparing for these agents that are gonna go looking for relevant data to kind of render a judgment, they’re still gonna have to train them.

They’re gonna have to really think about, you know, how to do that the right way. Now we may see different things evolve. Like I’ve talked a lot about the word rep website. I’m probably gonna write a column that suggests that maybe we need a new name called, you know, like a an inventory locker that’s kind of like very, very agent, agent, agent friendly. But but yeah, I think I think brands, yeah, everybody’s waxing poet have got agents, but I keep reminding brands like careful what you ask for on this one.

because you are not prepared and you are going to be really, really surprised at what these agents are recommending. And you’re going to probably lose even more control. So brands are going to have to really think about that one carefully.

Neville Hobson (51:24)
So to that point then, if AI agents increasingly recommend products, services, suppliers, even employers, companies to work for, for instance, what happens to traditional brand marketing?

Pete Blackshaw (51:38)
Well, think it’s gonna have to wrap around a lot of that. I mean these some of you know, listen, I mean branding has always been in the you know, content marketing’s been a big thing well before AI, but they will have to, you know, keep doing some of that, but they may need to dial down the BS factor, they may need to dial down the hyperbole, they may have to dial down the exaggeration.

I mean, here’s one of the things that’s happening. You’ve got two very interesting trends going on. You’ve got the answer economy, you got the creator economy. Everybody at con was gaga about the creator economy. And there’s no question the creator economy is creating massive reach. But hey, one of the interesting things about the creator economy, they do not index in answer engines. Maybe a little bit meta because they’ve got tick to they’ve got, you know, Instagram and but generally, you know, the creators are not getting the love from the answer engines. And why is that?

I think they’re very hesitant. There tends to be a lot of hyperbole and a exaggeration among the crater economy about what the products do. And I think and and sometimes they’re paid, but they’re not disclosed. And so it’s just it’s just it’s a it’s a less it’s a complicated area for the algorithms to kind of take seriously. And so I just think, you know, all these things are gonna have to be really, really carefully thought, you know, thought through, you know, as pr as brands try to

Neville Hobson (52:35)
Hm.

Pete Blackshaw (53:00)
You know, you know, I th I I probably haven’t used the word trust enough. I think what’s gonna be more important than ever goes back to our very, very conver very first conversation when we’re talking about the the rise of blogs. But yeah, brand trust will be critical. And I do think the brands that really think hard about what that means are gonna win. And I know brand trust tends to be a little fluffy. Every I’ve even had investors like, what the hell? How the hell the hell does trust sell cases? But we all know that.

Trust is the currency of advertising in all relationships. And I think AI is just gonna magnify that in a big way. So brands are probably gonna have to really double down in that particular area.

Shel Holtz (53:43)
What about B to B? is is it the same situation? do they need to think differently? No different.

Pete Blackshaw (53:47)
No different.

No different. I mean, every B2B supplier is using Chat GBT to vet other suppliers to vet. If anything, I think B2B is gonna get a massive turbocharge. I do think AI systems are, you know, you know, I I have to worry about that too. It’s like I got RFPs with other, you know, big companies, and you know, they’re kind of using AI to basically kind of, you know, do their research on us versus competition, but

No, I think it’s it’s kinda shy. I mean, I and I’ve done scorecards. I’ve done I have all sorts of indexes that I’ve created, including a B to B one on what are the best vendors across all these different areas, who shows up, who doesn’t. And now there may be certain my guess isn’t on the B to B side, Claude will again probably be the one that is most most focused on. Actually I th I think copilot isn’t bad either, but

But yeah, there probably will be some favorites that the procurement officers use as they’re trying to figure out who’s the right vendor that’s that’s that’s out there. But zero difference in my view.

Neville Hobson (54:55)
Hm. Okay. So what would you advise communication professionals to start doing differently tomorrow morning?

Pete Blackshaw (55:03)
Well, I think they need to look in the mirror, which is, you know, an AI is a mirror and they should, you know, really get their organization internalizing this new reality that your brand is as strong as its answers and these new influencers are shaping their answers. And so I would number two, I would tell every communications professional that they have more leverage than they realize. That brand website, especially the corporate website, which I think generally are more optimized for curiosity than brand sites. Brand sites are very optimized for conversion.

If you go to a corporate site, you know, Nestle.com, I think they’ve done a really, really good job. They even have a section called Ask Nestle, which I love, and have encouraged them to kind of take to the next level. But all that probably is more valuable than it was a year ago. And I would I wouldn’t, you know, and I think some of those things are underfunded. some of them are afterthoughts. Some of those are like, that’s the brochure, but that is really.

powerful. And I also think corporate communications in particular has a lot of leverage to lead because it’s really hard to get like fifty brands within the franchise to kind of like get their act together. And I do think the book of truth may be best developed at the corporate level. But then again, it has to be tomorrow’s definition of corporate communications. I think if you ask brands, they’d say corporate communications is is backwards. They slow things down.

They’re naysayers. They’re not a progressive force in the organization. They’re overly conservative. And if I were heading corporate communications, I would be, no, no, no, no, no. We can actually, we are the lever to win in the answer economy. We have always been sensitive about substance, you know, you know, doing what we say, checking off the compliance boxes. Those, those are all the things that really matter to the LLMs. So yeah, if I were giving that that.

Neville Hobson (56:44)
Mm.

Pete Blackshaw (57:10)
that college football speech to, you know, corporate communications, I would be saying, My friends, this is your day. And let’s look in the mirror and let’s go. And let’s make our CEO a hero because, you know, the the the stakes are going to go up. We’re not going to get the credit we deserve unless we’re more proactive. But we can. Something like that.

Shel Holtz (57:30)
Yeah, remember Richard Edelman saying that about social media and it just didn’t happen. Pete, you probably remember from your previous appearances that we always end with the same question, and that is what didn’t we ask that we probably should have, or that you were expecting us to?

Neville Hobson (57:31)
Yeah.

Pete Blackshaw (57:48)
gosh, what didn’t you ask?

I don’t know. Fair You you do I was surprised you didn’t ask, so Pete did you use AI to help write your book? You know.

Shel Holtz (58:02)
Yeah.

Neville Hobson (58:04)
But

but but you did. In fact, you got a really good page in the in the galleys that I saw explain yeah. Yeah, i that is super what you wrote, really, really and truly. It a it adds

Pete Blackshaw (58:08)
Did you like that? I love that page. I love that.

I love that. And I

did well the funny thing is like I’ve been listening, I mean, you know, sometimes I’ll take a chapter, throw it in a clod and say, Tell I’m fully shit. You know, it’s like but it was all me, but it did help me navigate. And I have this term that I use called dog walk journalism. I’ll take my dog on a walk and I’ll bark out my random thoughts. And AI is wonderful at connecting the first thought with the last thought and kind of giving you a starting point. But but I did have this really intense editor, her name was Angela Morrison.

And she was actually the editor, the partner to William Sapphire, who wrote the column on language. So she was really good. She had this really intense long island draw. And she’s Pete, don’t take it personally, but I am totally blunt. But my gosh, she like took me to town on indefinite pronouns. I thought I felt like I had never learned writing, but that was like the great, it was like a great human in the loop epiphany because she was hitting things that even the LLMs

Neville Hobson (58:59)
Yeah.

Shel Holtz (59:04)
Ha ha ha.

Pete Blackshaw (59:12)
Could not catch. And I I was reading the book. I was like, my God, I’m so blessed to have had a really good editors. So

Shel Holtz (59:19)
If I ever work with her, I’ll

Neville Hobson (59:20)
Brilliant.

Shel Holtz (59:21)
be sure to have my copies strunken white by my side.

Pete Blackshaw (59:24)
Yeah, yeah, yeah, yeah, yeah. Yeah. And if you know of any, you know, you guys bump into all sorts of folks and cor my one of my goals, I really want to wake up a lot of corporate communications departments. That’s that’s my sweet spot. I’ve always loved the balance of brand defense and offense. But the offense, the defense side is I I think more urgent and more challenging. So yeah, as you know, you know, I’m doing a lot of I’ll be doing a lot of wake up calls, speeches and workshops. But yeah, if you know folks that need the help, let me know.

Shel Holtz (59:53)
And how can people get in touch with you?

Pete Blackshaw (59:56)
just Pete at brandrank.ai or the answer economy dot com. or they just type my name into an answer engine and you know they can they can they can vet me first and but yeah, it’s in in I’ll I’ll give it to you as well when you advertise the the the the the podcast. But yeah, it was great talking to you guys. I miss I miss our conversations.

Neville Hobson (1:00:16)
Guys.

Yeah, likewise. That was good. Appreciate it.

Shel Holtz (1:00:22)
Yeah, thanks so much, Pete.

Pete Blackshaw (1:00:23)
You bet. Always.

The post AI, trust and the answer economy – Pete Blackshaw on the future of brand credibility appeared first on FIR Podcast Network.

Everyone from CEOs to politicians has been talking about the likelihood of AI-related job loss, and several companies have already let people go in anticipation that AI can do their work. Ford Motor Company is the latest to rehire those workers when AI proved inadequate for the job. Elsewhere, many of the managers who have let people go regret their decisions, and some companies are revising their hiring plans. To remedy the chaos, Neville and Shel discuss the importance of strategy and knowledge management systems, among other things.

Links from this episode:

• ‘Talent refresh’ | Ford rehires human staff after AI quality-check tools fail to deliver
• Ford rehires human engineers after AI fails to match quality checks
• Return of the ‘greybeards’: AI backfired – so Ford had to rehire humans
• Ford Has Been Rehiring Quality Inspectors After AI Fell Short
• Ford rehires ‘greybeards’ after AI tech fails to deliver

The next monthly, long-form episode of FIR will drop on Monday, July 27.

We host a Communicators Zoom Chat most Thursdays at 1 p.m. ET. To obtain the credentials needed to participate, contact Shel or Neville directly, request them in our Facebook group, or email [email protected].

Special thanks to Jay Moonah for the opening and closing music.

You can find the stories from which Shel’s FIR content is selected at Shel’s Link Blog. You can catch up with both co-hosts on Neville’s blog and Shel’s blog.

Disclaimer: The opinions expressed in this podcast are Shel’s and Neville’s and do not reflect the views of their employers and/or clients.

Raw Transcript:

Shel Holtz
Hi everybody, and welcome to episode number 521 of For Immediate Release. I’m Shel Holtz

Neville Hobson
And I’m Neville Hobson. Here’s a story that should make every one of us pause before we get too comfortable handing things over to AI. Ford, the automaker, has just rehired somewhere between three hundred and three hundred and fifty veteran engineers. Note the word rehired. The company had let them go in recent years as it leaned into AI-driven quality checks. Ford calls them greybeard engineers. That’s not a throwaway nickname. It’s the whole point of the story. These are the people with decades of experience across multiple product cycles, and Ford let a lot of them go only to discover it needed them back because the AI wasn’t working the way Ford expected. We’ll look into what happened right after this  Charles Poon, Ford’s vice president of vehicle hardware engineering, put it plainly on a call with reporters. Here’s what he said: “Mistakenly, we thought that by just introducing artificial intelligence and ingesting the design requirements that we had, that would produce a high-quality product.” Think about that for a moment. Ford didn’t skip a step. They fed the AI everything that was written down, every design requirement, every documented specification. It still wasn’t enough. And it wasn’t just one system. Ford had installed around nine hundred AI-assisted cameras on the production line specifically to catch quality issues. Nine hundred cameras, and still they couldn’t replace the trained eye of an experienced technician who knows what a problem looks like before it becomes a visible defect. Ford’s chief operating officer, Kumar Galhotra, added more context. He said the company had been leaning more and more on automated quality systems, and the results were disappointing. Teams across software, hardware, manufacturing, and supply chain had also been working in isolation from each other, which meant defects were being caught late and fixed under pressure rather than prevented early. Galhotra described this as a find and fix mentality that Ford is now trying to move away from towards genuinely preventing problems before they start. The returning engineers sit right at the center of that shift. They now run mandatory weekly quality and design reviews, hunting for failure points before a single part reaches the factory floor And here’s the part I think matters most for us. A lot of the people who held that hard-won judgment had already walked out the door to suppliers, to retirement before anyone at Ford thought to capture what was in their heads. Poon admitted as much. “Over prior years, we didn’t pay as much attention as we should have to the experience of our most knowledgeable engineers who have been with us through many product cycles,” he said. So Ford had to buy that expertise back three years into this process at real cost. Was it worth it? By Ford’s own numbers, yes. The company has just topped the J.D. Power Initial Quality Survey for mainstream brands for the first time since twenty-ten. That’s sixteen years. CEO Jim Farley says the rehired engineers are already contributing what he called literally hundreds and hundreds of millions of dollars in savings, largely through reduced warranty and recall costs. Ford’s even projecting around a billion dollars in cost reduction this year on the back of this quality push. Now, here’s a tension worth sitting with. This is the same Jim Farley who said publicly on other occasions that AI is gonna replace rough-roughly half of all white-collar jobs. And yet here’s his own vice president standing in front of journalists explaining that Ford’s entire quality turnaround depended on bringing back the very human expertise the company thought it could do without. To be clear, this isn’t really a story about AI failing and humans winning. Ford isn’t walking away from AI. Those returning engineers aren’t just doing inspections. They’re training junior staff, and they’re reprogramming the AI tools themselves, feeding them the judgment that design requirements alone couldn’t capture. It’s a hybrid fix, not a retreat. But for anyone in our line of work, comms, knowledge management, anyone thinking about where AI fits into institutional expertise, there’s a sharp lesson underneath all of this. Documentation isn’t the same as judgment, and once the people carrying that judgment are gone, you don’t get it back for free or quickly or easily. I think there’s a bigger question here, too, about how organizations are handling this handover between human expertise and automation, and whether Ford’s experience is a one-off or a warning sign for a lot more companies than just car manufacturers. Shel

Shel Holtz
Yeah, I think it is a warning sign. But I, I don’t think it’s a trend necessarily, the idea that AI AI layoffs are being reversed everywhere. Yeah I’d just be careful about overstating that. There’s really only a handful of well-documented company examples of this. I think it’s easier to say that the way many organizations overestimated how quickly AI could substitute for the experienced judgment of their staff, I think that’s a reasonable way to look at it. Increasing number are recalibrating toward AI human collaboration rather than there are examples though. IBM has reversed course. They didn’t rehire the same people, but they’ve really reversed course on this whole replacement idea. An AI system deployed to take over HR work handled about 94% of incoming requests, but the 6% it couldn’t resolve including situations in- involving ethical judgment, really revealed the limits of all of this into the hands of a large language model. And then the company announced that it planned to triple its US entry-level hiring this year. That’s a pretty significant reversal. Klarna’s the one that … that’s the poster child for all of this. They were one of the first to announce that they were going to replace their customer service with AI. A year later their CEO publicly reversed course, admitting that customer experience had gone down the tank, quality had fallen the company had over-prioritized cost savings which most companies seem to be doing. They’re looking at cost savings and not other ways AI could really improve things or even help the organization grow and that human customer service remained essential. So they went back to hiring customer service representatives, and they expanded their human support. They la- even reassigned engineers and marketers into customer support roles while they were busy rebuilding the support organization that they had decimated. CEO, I think it was he who was quoted saying, “Cost, unfortunately, seems to have been too predominant evaluation factor.” that said I think it is worth noting that according to one research organization, I hadn’t heard of them before, but OrgView, 39% of business leaders made employees redundant due to AI deployment, and among that number, 55% admit that wrong decisions about those redundancies made, 32% of US hiring managers said they eliminated a role primarily due to AI later rehired for the same or similar positions, that according to Robert Half. This is definitely something we need to be looking at. I think what Ford has done is, as you say a warning sign, but I don’t think there’s a clear trend yet that people who off in order to accommodate AI are suddenly reversing and rehiring yet

Neville Hobson
No, I agree. That doesn’t seem to be a trend. What is a trend is the laying off element of it as opposed to rehiring. So the… I think there, there’s a good question for our audience in all of this. How many organizations right now are automating roles without first extracting what the people they’re letting go know, their knowledge? Ford’s mistake wasn’t using AI, I mentioned earlier. It was letting the knowledge holders leave before capturing anything from them. That’s a sequencing failure, not a technology failure. So is knowledge capture before AI rollout ever ac-actually built into transformation plans, I wonder? Or is it always an afterthought that only gets addressed once something breaks?

Shel Holtz
It’s an interesting question.

Neville Hobson
Yeah.

Shel Holtz
when we first started this show 21 years ago, knowledge management was a big issue, and we talked about knowledge management and knowledge management systems, and they have fallen by the wayside even though there are still efforts to build them out. I think the need for clean, consistent data in order to run AI inside your organization is bringing the idea back, although not with the kind of notoriety that it had. There were books being written about knowledge management back 20, 20 years ago. But knowledge capture is an interesting thing because, there’s so much ta- tacit knowledge walks out the door and goes home every night. It’s not implicit knowledge that you can store in a database, and this was the problem with knowledge management systems, right? Is you’re trying to capture tacit knowledge, and it had to be tagged, which meant the people looking for it had to know which tag was used in order to retrieve it. That knowledge could be sitting there, but if you’re searching with the wrong tag, you’ll never find it. So it, it remains a challenge how to do this. I remember one effort at knowledge capture. Was it Intel? I’m gonna struggle to remember, but it was an early wiki where people would just leave their knowledge that occurred to them. “Oh, this is how you do this,” and they were trying to capture it that way. I don’t know if that’s still around. I never hear about it anymore. I- like I expect, I can’t even remember for sure what company it was, but have been efforts at this.

Neville Hobson
Yeah

Shel Holtz
and with the AI situation and companies like Ford finding the knowledge isn’t there once the people leave and the AI isn’t equipped to handle everything just based on was in the databases that it had been fed, I think we’re gonna have to revisit this whole idea of knowledge management and get it right this time because it’s still far from perfect

Neville Hobson
Yeah. Thinking about Jim Farley and what he said that AI will replace half of white-collar work, while his own VP describes a turnaround built on rehiring the humans they’d let go. I-is this Ford being inconsistent, or is it actually a realistic picture, AI displacing some roles while creating new dependency on a smaller pool of s- pool of senior experts? I wonder if that’s it. There’s also a related point to that. Could this be a warning? You, y-you mentioned– You used that word a minute ago in this case about h-hollowing out effect. If companies keep pushing out mid-career and senior staff in favor of AI, who trains the next generation of greybeards when today’s greybeards retire for good? ‘Cause that will happen sooner or later.

Shel Holtz
There’s also this idea of institutional knowledge that is not necessarily captured in any systems. It’s because they have been there, as was pointed out in this article, through multiple product cycles. There are things that they learned that are not a specific quality measure or whatever it is that they’re using in their work that now is gonna be done by the AI. They bring that institutional knowledge to the job, and y- you may not need as many of them as you had before if the AI can legitimately do some of this work. But some of those people who have been there through those product cycles and have acquired that institutional knowledge, they’re still gonna need to be there. I don’t know how you capture institutional knowledge. I have seen this in an organization that shall remain unnamed, but that you and I are b- both very familiar with, that, that hollowed out staff and let its institutional knowledge go, and is paying a dear price for that

Neville Hobson
Yeah. It got me thinking a bit about I guess drawing upon some science fiction movies that I’ve seen over the years but also now looking at where we are with technology tools that make it very easy for people to literally dump their knowledge about something into a device or a system that records that saves it. Could we be seeing a, the beginnings of something or the idea certainly that may catch on with people that this needs to be built into behaviors in an organization that depending on your role, and I can’t say it could be everyone, but maybe it should be, that you’ve got some means that you work on a project and part of your in a sense, your the kind of conditions of your employment, let’s say, is that on completing a project or planning a project and then com- wha- whatever it might be, you’ve gotta record your thoughts on the planning and execution of that project how you did this or that. And that’s then saved. Okay. I haven’t– I’m not even getting into privacy i-issues or data protection or none of that. That may well be the case. I’m thinking of one science fiction film I saw where, a few, some years ago now, where people had, It reminds me of Plaud, actually, a little credit card sized tool.

Shel Holtz
say

Neville Hobson
Yeah.

Shel Holtz
that. Yep

Neville Hobson
That they spoke into, recorded something. It then saved it to their account, let’s say, on their employer’s website or someplace or whatever it might be, that then broke it down into all the constituent elements that the company needed to have in order to retrieve that information on demand or make use of it in some other way. So some of the tech exists to do that, but certainly not on an organized scale such as what we’re discussing that might be. But how long might it be before that happens?

Shel Holtz
Aside from the privacy concerns, wearing a device that captures everything you say, having all of that from all employees fed to an AI that’s able to sort it out and put it in the appropriate place so that now that becomes part of its knowledge base, I can see that. I just can’t see employees tolerating it very well. I certainly wouldn’t want to have every word I’m saying during the day recorded and saved by the organization, and I’m a senior executive. That’s just ethically wrong I think. But technically I think we’re not that far away from

Neville Hobson
No, we’re not. We’re not.

Shel Holtz
do that now

Neville Hobson
You raise a good point but I would counter that in a sense arguing that it’s gonna be if you don’t do it, someone else is gonna do it, and you’re out of a job if you don’t do that. I’m thinking of some of the things that you see around you nowadays as a matter of course, ranging from things like police, ambulance workers fire department people wearing video camera, body cams that record everything. I have a friend of mine who’s just bought one that he feels safe wearing this on his commute to work on the train. He goes to London and then on the underground train. I can, I can–

Shel Holtz
use case. These are, these f- yeah I think,

Neville Hobson
it’s not. It’s not. It’s rec- it records the picture of him. That could be– The purposes might be very different, but the tech would be the same.

Shel Holtz
Oh, the text’s the same. The

Neville Hobson
Yeah.

Shel Holtz
is

Neville Hobson
Yeah. For now it is. Yeah, it is. But this could become a matter of course. I’ve considered that too. If I were still actively working in a traditional job, getting in a commute to London or whatever it might be, I would probably get a body cam

Shel Holtz
Yeah, the okay, the use case there is voluntary, right? You choose

Neville Hobson
I do have that choice

Shel Holtz
Think of Meta, which was capturing the keystrokes of every employee in order to train its models, and the opposis- opposition to that grew so loud that they recently said, “Okay, this is now a voluntary program. Only employees who opt in will have their keystrokes recorded.” And it– now you’re talking about every

Neville Hobson
Yeah, I know, but,

Shel Holtz
the workplace?

Neville Hobson
sure.

Shel Holtz
gonna happen. Yeah.

Neville Hobson
so this is– enters that bigger debate precisely on is it gonna happen or is it not? So in the case of Meta, what they did, I’m thinking back now to the Cambridge Analytica scandal of twenty eighteen, they did this ov- covertly without telling people, and then they lied about it all. So why the hell would you work for a company like that in the first place? That, crosses, crosses my mind. But

Shel Holtz
Yeah

Neville Hobson
I think the one other point occurs to me that the in the case of Ford, that has got me thinking. The fix they had, i.e., rehiring the people they, they got rid of, works because those engineers were still available to rehire, right? So what happens to the next company that has the same realization five or ten years from now when the generation with that tacit knowledge has genuinely retired and isn’t coming back? That’s arguably the real warning sign, not this instance, but the next one

Shel Holtz
Oh, absolutely. They’re gonna have to go for the next best thing, which is hiring humans that can handle the more complex problems that arise, but they don’t have the institutional knowledge. They haven’t been through any product life cycles. Maybe they hire away from competitors. Maybe they hire their old engineers back by offering them more money than they ever dreamed of, but yeah, that sort of defeats the purpose too, doesn’t it? No, I think what has to happen is that the companies that are considering replacing people with AI don’t just count the number of who are doing the job and how much an AI can conceivably do, and then get rid of the equivalent number of staffers. You’ve gotta be really strategic about this. I think you need to inventory all of the tasks that you’re talking about performing and identify which of those are better done by AI. Heaven knows there are things that AI is not good at,

Neville Hobson
Yeah

Shel Holtz
pretty widely recognized sets of activities. So looking at what you’re gonna need people for and then determining, okay, if we’re gonna let people go how many we still need in order to avoid the kind of outcome that Ford experienced? And I think if they’re strategic, if they apply some formulas to this again, inventorying absolutely every task you’re gonna be looking at replacing and figuring out which of those are going to work with AI you’re probably gonna end up making better decisions and not have to do what Ford did. The other thing that I would look at though is how does all of this align with your values? Because no matter what you do, it is in conflict with your stated corporate values, which are hanging on the wall in the conference rooms and, employees have copies of them, and in my company, they’re on every truck that’s out there you’re gonna end up with a very disengaged cynical workforce

Neville Hobson
Yeah. The cynical part of me suggests that’s actually happening a lot already. G-question mark, do they really believe those values on the side of the trucks down the road, all that kind of stuff? So it’s a kind of fluid environment we seem to be in. And I’m wondering w- as well, will we begin to see, I don’t know on your CV or your resume on LinkedIn one of your major selling points is gonna be the fact that you have deep institutional knowledge. You probably wouldn’t wanna say about your employer, but what you really want to be saying is about the industry or about something that sa- that kinda says, “I’m very portable from the get-go.” So maybe we’re gonna see that

Shel Holtz
Oh, could be. It would certainly be better than open to work as a little arc on the pr-profile photo on LinkedIn. And that’ll be a 30 for this episode of “For Immediate Release.”

 

The post FIR #521: AI Layoffs Are Here. Wait. Strike That. Reverse It. appeared first on FIR Podcast Network.

In the long-form FIR episode for June, Neville and Shel consider the causes and implications of surging anti-AI sentiment in the US (which is also growing in other developed countries), as well as the increasing use of “shadow AI” in organizations. Other reports include studies documenting the continued erosion of trust in mainstream news media, the growth of personal branding among communication professionals, a shocking self-inflicted reputation crisis for a UK business, and evidence that employees aren’t reading your internal communications (unless maybe they are). Dan York shares information on Collections in the Mastodon 4.6 release and the W Social situation in his Tech Report.

Links from this episode:

• ‘Shadow AI becomes a massive enterprise liability’: New study claims most of us are now using unauthorized AI tools at work
• FIR #510: Should Companies Embrace Shadow AI?
• FIR #419: Is Shadow AI an Evil Lurking in the Heart of Your Company?
• The Rise of Shadow AI is a Double-Edged Sword for Corporate Innovation
• Americans Have Turned Against AI in Incredible Numbers
• AI’s Public Relations Emergency
• AI Data Centers and the Public Relations Challenge for Business Owners
• Wowcher apologises after email appears to reference crocodile attack on toddler
• Digital News Report 2026
• From Invisible To Influential: The Personal Branding Shift In Corporate Communications
• Wowcher apologises for email referencing toddler crocodile attack
• Wowcher ‘extremely sorry’ for crocodile attack email
• Wowcher apologises over email that referenced crocodile attack on boy
• LinkedIn post (Queen of CRM): “I’ve had 16 messages about this email…”
• LinkedIn post (Flo Powell): Wowcher ‘extremely sorry’ for crocodile attack email
• The Attention Recession: Why Your Employees Aren’t Reading What You Send
• State of Workplace Communication 2026: Why 44% of Employees Tune Out

Links from Dan York’s Report

• Designing Collections
• Mastodon 4.6
• The Untold Story About W Social: Unconventional Beginnings, Strategic Pitches and Conflicting Signals
• W Social, Public Institutions and the Theater of European Digital Sovereignty
• W Social, Fictional Metrics and the Beauty of Open Data

The next monthly, long-form episode of FIR will drop on Monday, July 27.

We host a Communicators Zoom Chat most Thursdays at 1 p.m. ET. To obtain the credentials needed to participate, contact Shel or Neville directly, request them in our Facebook group, or email [email protected].

Special thanks to Jay Moonah for the opening and closing music.

You can find the stories from which Shel’s FIR content is selected at Shel’s Link Blog. You can catch up with both co-hosts on Neville’s blog and Shel’s blog.

Disclaimer: The opinions expressed in this podcast are Shel’s and Neville’s and do not reflect the views of their employers and/or clients.

Raw Transcript:

Shel Holtz: Hi everybody, and welcome to episode number 520 of For Immediate Release. I’m Shel Holtz in Concord, California.

Neville Hobson: And I’m Neville Hobson in Somerset in the UK.

Shel Holtz: And it’s good to be back with you for our long-form episode. We really enjoy doing our short midweek episodes, but these are an opportunity to dig into some meaty topics. And we have six for you this week. Obviously, we’re going to be talking about some artificial intelligence, but not exclusively. So we have some other communication-focused topics to share with you, and some comments from listeners from the last month’s worth of episodes. And to get to those, Neville, how about a recap of what we’ve talked about in the last month?

Neville Hobson: In the long-form episode 515 for May, on the 25th of May, we led with the rise of AI agents, the harms they could cause, what companies should do to ensure these agents deliver benefits, and how communicators can take a leading role in addressing the issue. We also talked about AI copyright lawsuits, Google’s search overhaul, what’s becoming standard media relations practice on podcasts, the question of whether the time is coming for value to be at the forefront of client billing, and the rise of short-form video clippers. A lot of content in that bumper issue. Hefty but good, as we like to say. And then The Economist is building two versions of its web presence: one for human readers, one structured for AI agents. In FIR 516 on the first of June, we discussed what this means for communicators and raised an important counterpoint. Websites aren’t going away. We said the answer is to do both, not abandon one for the other. And we have at least one comment on this one, don’t we, Shel?

Shel Holtz: We have several comments on this one, starting with Sylvia Cambié, who says: “A really interesting episode. Your point about the need to be deliberate when we write copy for websites and think about what an agent would extract is fascinating. Here’s a task that communicators can do well. Great to see new tasks like this emerging for comms. It is funny to hear that AI likes Q&As. When I was a journalist, this was considered a real no-no, a sign of lazy journalism. How times change.” By the way, The Economist has published a great article by Harvard Kennedy School fellow Shui Fang about the world entering the age of machine audiences and agents. And Neville, you replied that her point about Q&As is spot on, and you hadn’t thought about it from a journalism angle before. It’s a good example of how context changes everything. What signals laziness in one setting becomes good or best practice in another. And yes, communicators are well placed to take this on. Structuring content with clarity and precision is what good communicators do. The agent readability requirement just makes the skill more explicit and more consequential. Then we have a comment from Sally Getch, rhymes with “sketch.” She says: “I started this comment on the website, but realized I needed to revise it. My first thought is, WTF is wrong with The Economist’s regular website that it’s unintelligible to AI agents? In my experience, AI does a pretty good job of reading and understanding websites, and it seems to be able to find and do things that the search engines we have all spent decades trying to appeal to could not, like transcribing PDFs and audio files. We use them for those purposes ourselves. Likewise, images with good alt text improve the understanding of both bots and humans. It felt like a flashback to the days of ‘we need to make a separate mobile website.’ I don’t think you need a separate site, but you might need a better one. I asked Stefan about this” — that’s her husband and a software developer — “and he said that the reason for the markdown is because it’s fewer tokens for the agent to consume and therefore costs less. There are some new and therefore not widely tested WordPress plugins that can convert your pages to Markdown and index them to LLMS.txt. If you edit a page or a post, they generate a new .md file. Another thought I had was that one thing that might interfere with agents ingesting content on media sites is ads. They sure do that for humans.” And then Vincent Bruneau left a short comment saying: “Parallel content architectures for human readers and AI agents is the clearest signal yet that the two audiences have genuinely diverged. And if The Economist is doing it, the question for every communications team is not whether to think about this, but how far behind they really are.”

Neville Hobson: Good comments. I think Sally’s in particular had me thinking. And I think all I’d say to Sally’s really good, insightful opinion there is, I recommend you read The Economist article explaining in considerable detail why they’re doing this. I think we link to that. The trouble is it’s behind a paywall, but there are ways around that kind of thing. Anyway, thanks to those commenters. So then in episode 517 on the ninth of June, we looked at what communicators should do when leadership makes a loud public bet that doesn’t pay off. Yes, it’s AI we’re talking about. And what happens when the bills start piling up and companies realize the cost isn’t tenable? Can communications repair the resulting damage from such a management failure that wasn’t a technology one? Partially, we said, but only if leaders are willing to be honest about what happened and why. And there are comments.

Shel Holtz: One comment, and this is also from Vincent Bruneau, who has also left a comment on 518, and I just want to tell Vincent, thank you for being such an interactive participant in our episodes. It’s great to see you here. Vincent writes: “The gap between the loud public bet and the quiet walk-back is where employee trust goes to die, and communications can only repair it if leadership is willing to be honest about what actually happened. Partially is the right answer, and probably more than most organizations will achieve.”

Neville Hobson: Terrific. So next: PR misread social media in 2007, and the internet in 1995, and desktop publishing before that. The disciplines that grew from these were largely built by people outside the profession. Are we about to do it again with AI? In episode 518 on the 15th of June, we explored why PR agencies still seem unable to figure out billing models to replace the now-useless hourly rate, we would argue — and we did — and what they should be doing, noting that time freed up by AI only has value if organizations know what to replace it with. That’s a very concise summary of that episode, but we talked about a lot in that episode. And we have comments, right?

Shel Holtz: Again from Vincent Bruneau. He says: “‘Time freed up by AI only has value if organizations know what to replace it with’ is the line that exposes most current AI strategy in PR. Efficiency without redirection just produces idle capacity, not transformation. The return to relational, face-to-face work as the actual opportunity is the most hopeful and least obvious takeaway.”

Neville Hobson: Now, we have known about the media bias effect for decades — the belief that the media is biased against your side of a debate. New research finds that the same belief applies to misinformation. In FIR 519 on the 22nd of June, we looked at what this hostile misinformation effect means for organizational communicators, discussing what strategies might look like, including pre-bunking and the value of calm, rapid response. If you look up pre-bunking, by the way, you’ll get an answer on Google. So now you’re up to date on FIR episodes.

Shel Holtz: Yeah, and by the way, I was on a panel at the PRSA Public Affairs and Government Section Summit in Covington, Kentucky, right across the Ohio River from Cincinnati. We had the panel on Friday, just yesterday. Good God, I was in Kentucky yesterday. And pre-bunking came up there as a way to address misinformation, disinformation, and malinformation. It’s really just the notion that you can anticipate what people are going to attack you on. And if you already have the content that addresses that, it becomes very easy to point to it. And you don’t look reactive when you’re pointing to content that’s already there. You’re not inventing new stuff to address it. So that’s, I think, an important practice for communicators to consider given the state of the media environment these days. Circle of Fellows is going to be posted very, very soon. We did record it. It was two episodes on the same day. Brad Whitworth hosted the first one, I hosted the second one. And the reason for this was that this is the episode where we introduce our new fellows, and there are five of them, and they are across time zones. And the only way we could make this work for people who are in Australia and all over the world was to break this into two. So those will be posted soon, and you’ll have the opportunity to meet our five new fellows. The next episode of Circle of Fellows — episode 131, and we do this once a month, so 131 of these is, I think, noteworthy — that will be on Thursday, July 23rd, at noon Eastern time. The topic is the evolving media landscape and the value of ethical journalism. I’ll be moderating that one with Diana Degan, who is one of our 2026 class of fellows, Ned Lundquist, Martha Muzychka, and Jennifer Waugh. So if you would like to participate in that in real time, mark that on your calendars. That covers our pre-topic discussion. We’ll start the conversation around our six topics right after this.

Neville Hobson: Shadow AI is a topic we’ve returned to more than once on For Immediate Release, and with good reason, because the story keeps developing and the numbers keep getting harder to ignore. Shadow AI is the unauthorized use of artificial intelligence tools, applications, or models by employees without the formal approval, monitoring, or oversight of an organization’s IT or security teams. It typically happens when workers use public, consumer-grade tools such as ChatGPT, Claude, Gemini, or third-party browser extensions instead of tools approved by the employer — Copilot, for instance, a common one — to speed up tasks, brainstorm, or analyze data. Cast your mind back to July 2024, when in FIR 419 we asked whether shadow AI was an evil lurking in the heart of your company. At the time, a Cyberhaven report had found that 27.4% of the content employees were feeding into AI tools was sensitive: customer data, source code, confidential HR records. It was a striking figure, and it pointed to a tension that was already building between what employees wanted to do and what their employers were prepared to sanction. By February 2025, in FIR 449, we were reporting that employee use of shadow AI was surging — half of all employees, some studies were suggesting. The appetite was clearly there. The question was whether organizations were keeping pace, and by most accounts they weren’t. Then in April this year, in FIR 510, we put a sharper question on the table: should companies simply embrace shadow AI? Not fight it, not just manage it, but lean into it? Because by that point it was becoming clear that the crackdowns weren’t working, and the productivity gains employees were quietly achieving were real. Now we have new data. And it moves the needle again. A June 2026 survey carried out by Wakefield Research for PagerDuty — a digital operations platform that automates incident management, alerting, and on-call scheduling for IT and DevOps teams — reported that two-thirds of US workers, that’s two in every three, are now using AI tools at work that their company hasn’t approved, in spite of knowing the rules. More than half received informal warnings to stop. Nearly half faced formal consequences — official warnings, disciplinary action — and they carried on regardless. Perhaps the most telling finding is this: 88% of those workers have shared work-related information with public AI systems. We’re not talking about using a tool to draft a meeting agenda. People are uploading emails, sharing meeting notes, entering customer information, and in nearly a third of cases, inputting sensitive business documents, financial data included. There’s also a striking confidence gap emerging. Nearly three-quarters of workers and 77% of senior leaders believe they understand AI better than their own tech teams. Whether or not that’s true, it tells you something important about the dynamic inside organizations right now. This isn’t a case of employees feeling lost and reaching for unauthorized tools out of confusion. They’re reaching for them out of conviction. And this is worth noting: one reason employees may feel less obligated to follow AI rules is the perception that company policies are inconsistently applied. According to PagerDuty’s report, while 86% believe their company has formal AI policies in place, more than four-fifths — 81% — believe those rules are applied differently to leadership than to the rest of the workforce. So here’s the question I want to ask. If two-thirds of your workforce is already doing this, if warnings, policies, and even disciplinary action haven’t slowed it down, is the era of the company controlling its employees’ AI use effectively over? Is the current wave of anti-AI sentiment sweeping the US playing a role here? Shel, we’ll be talking about that in a bit. If the era of the company controlling its employees’ AI use is over, what does responsible AI governance actually look like now?

Shel Holtz: AI governance is just in complete disarray, I believe, right now. I’m sure there are some companies that have their AI governance in good shape, but I think overall — and the research seems to bear this out — it’s chaos out there. I think you probably have a variety of different situations from organization to organization. You have governance that people look at and say, “This is ridiculous.” You have governance that employees are not aware of, or that has not been well communicated. I think there’s a variety of reasons that we’re seeing this — governance that even leaders are not adhering to, and you alluded to this, and that’s very visible. You hear stories of employees being told, “You have to use Copilot because we’re an Office 365 shop and we get Copilot with it, and it’s been extended to all of your Office 365 tools, your Outlook email, your Microsoft Word and PowerPoint and Excel — all of these things are now AI-enabled, so use Copilot.” And then you hear that the executive vice president for operations is happily using Claude all the time, while you also have somebody in HR who’s using ChatGPT, and employees roll their eyes and say, “Well, if they’re going to do it, I’m going to do it. I’m just not going to tell anyone.” They’re using their own accounts or billing it through their expense system for twenty bucks a month, and nobody’s even noticing, because who’s paying attention to a twenty-dollar-a-month charge? It’s terrible. And I think there’s a lot that has to happen, and it should happen, and it must happen, in order for organizations to get their arms around this. The first is more communication from leaders about their expectations. We just had a town hall where our CEO told employees explicitly, “We want you to use this.” He talked about caution about exposing client information or anything else that’s proprietary. He talked about the fact that our Copilot account allows us to keep all of this data in the company. It doesn’t get exposed to the models for training purposes and the like. And that’s one of the reasons we want employees to use that. And that was the caution he gave: if you’re using the others, you’ve got to be really, really careful about that. But I also think that employees need to have a voice in this. If they’re going to embrace it, they need to feel like they own it. And again, I’ll talk about where I work. And I’d love to take credit for this, but this was not my doing — there is an AI committee. And this is not IT people and leaders and the like. We have project engineers and project managers, frontline people on this, including one or two who were skeptical at the outset. And it’s a very enthusiastic group, and we’re planning a company-wide activity because we want employees to have that voice in this. We want them to feel like they’re part of what the direction is with AI — what tools we adopt, what policies we adopt. It’s like anything else in the organization. I mean, think about value statements, for example. If employees feel like they had a say in determining what the company’s values are, they’re going to embrace them. If it’s leadership coming out saying, “Here are our values, live these,” and employees go, “Well, wait a minute, I don’t see that in practice in the organization, and they don’t align with my values,” then you’ve got trouble. It’s the same thing here. So if this is foisted on employees who are already figuring out other ways to do this that are better for them, you end up with all kinds of problems. One, for example, is you’ll find that there are employees who have solved big problems in their jobs and made themselves more efficient and more productive, or have been able to grow something beyond where it was using AI, and they don’t share it, because they don’t want to admit that they used some tool that isn’t authorized in the organization. So you have fifty other employees doing the same job the old way and not benefiting from what this first employee learned. That’s terrible. We need to get our arms around this. And I think communicators have a huge role to play here, because let’s face it, this is not about policy. This is not about technology. This is entirely about communication.

Neville Hobson: Yeah. And I think the policy hypocrisy point, if I can call it that, needs pushing on directly. According to the survey, if 81% of workers believe AI rules are applied differently to leadership than to everyone else, that’s not a compliance problem. It’s a legitimacy problem, surely. No AI governance framework can work if employees don’t believe it applies equally to the people setting the rules. So that makes total sense to me — it won’t work. Do you think, if this is widespread — and there’s the worry, it seems to me, if it’s widespread — do you think any organization can recover trust on this without visible, demonstrable accountability at the top? Where does the buck stop in that case?

Shel Holtz: Absolutely there needs to be visible accountability at the top. But if there is, yes, you can recover trust. You lose trust a lot faster than you can rebuild it. So rebuilding it is going to take time, it’s going to take a plan, but it absolutely can be rebuilt. And again, I think this is where communicators come in, to say, “Okay, let’s develop a plan and a strategy around this.” Does your company have a committee that engages the front line in the discussion that is leading to this? If not, consider that. Does your company communicate the policies well? Does it share success stories with employees? There needs to be a strategy for this. You can’t just throw it out there like, you know, a new HRIS — we’ve adopted Workday, you let everybody know once, and they start recording their time there and requesting their PTO there, and everybody figures it out, and it’s no big deal. This is not that. We need to have a long-term strategy that we can adapt as things change, because as you know, in the AI world things change a lot, quickly. I don’t know if you read that Sam Altman has announced that there are going to be massive changes to the ChatGPT interface. He said the chatbot is over — this is an agentic thing now — and what you’re going to see on ChatGPT will reflect that. So people who think of AI as a place where you go type a query into a box — I’m sure there’s going to still be a way to ask a question and get an answer, but that’s not the focus anymore. What does that do to employees who are going to a tool and seeing these changes? We need to be able to pivot pretty quickly. But we need a plan that will accommodate that kind of change, but also move us forward in getting the benefit from AI and also rebuilding that trust. And by the way, one of the things I think employees would love to hear — and I don’t remember where I read this, it was just in one of the newsletters I got, it may have been Shelly Palmer — is that we’re not talking enough about using AI to grow the organization. We talk about being more efficient and saving money and saving time, which is all great. But AI can actually help your organization grow. And we’re not talking about that. We’re not talking about how to do that. We’re not talking about the role employees could play. And if employees knew that that’s what they were contributing to, I think there might be a bit more enthusiasm around it.

Neville Hobson: Let’s take a look at this confidence gap a bit. This is where nearly three-quarters of workers believe they understand AI better than their own tech teams. This strikes me as genuinely new territory. Shadow IT was about convenience, right? This feels more like a values clash — employees who believe they are the more capable party, acting accordingly. Is this the moment, do you think, where the traditional model of IT as gatekeeper finally breaks down for good?

Shel Holtz: Yes and no. I think those employees are right to a great extent. They know how to use this tool for their job better than IT ever could, because this is not Excel, right? It certainly isn’t something like an enterprise resource planning system or a customer relationship management system, where IT is clearly going to be an effective gatekeeper. This is where every employee is going to use it differently based on their job, based on their role, their department, their function — and they know best. And I think where IT still needs to be the gatekeeper is on things like cost. If employees are out there creating agents that are just continually looping 24 hours a day, you’re going to burn through a lot of tokens, and the company’s going to have a pretty considerable impact on their bottom line. So there’s absolutely a role for IT to play, but it’s on the technical side, not the application side. How it’s used — I don’t think IT can help you much there at all. They’re not experts at prompt building. They’re not experts at skill or agent building. That’s really not their job. They’re looking at the nuts and bolts of it. So I think there’s still a role there, as a gatekeeper on that side of it. I think policies about how much you use agents and how often you run them and how many tokens you burn through, and education around that — that’s probably an IT thing. And communicators should be working with their IT teams to convey that information. But in terms of how I’m going to use this — man, IT can’t tell me how to use this as a communicator, and I don’t think they have any interest in doing that either.

Neville Hobson: That’s good. Although I would argue that there’s probably a learning experience ahead for IT in that regard, because IT has had a history, I suppose, of dabbling in stuff that is not their domain at all. They see everything as an IT project. So some behavior change is due, I think.

Shel Holtz: Heck, yeah. I remember in the early days of email, there was a company I was doing consulting for that had a CIO who had to approve every email that went to all employees. And I didn’t work there very long, because I looked the CIO right in the eye and I said, “Really? Does your printer approve everything that goes out in print?” Because that’s essentially what it was, right? But no, I think there are more IT departments these days that recognize, especially with AI, that their role is not to tell engineers how to use this or accountants how to use this. Certainly our IT department is very supportive of having employees figure out what the use cases are. They’re not even dabbling in that. Well, let’s stick with this topic of AI, because AI has lost the public. We’re not talking about some public skepticism. This is a flat-out rejection by the vast majority of the American public. And Neville, when we talk about this, we’ll also talk about the UK and Europe. But how vast is vast? There’s a new Pew survey out this month that found that just 16% of Americans believe AI will have a positive impact on society. Sit with that for a minute. 16%. Forty percent expect the impact on society to be negative, and about a third think it will personally harm them. Right? Got that? A third think that AI is going to be harmful to them. The people most hostile to AI are the young. Among Gen Z adults, nearly half think AI will be bad for society. And yet that same group uses it more than anyone else — two-thirds of them. Alex Kantrowitz at Big Technology makes the point that this is the real emergency, because the attitudes people form in their late teens and early 20s are the ones that stick for life. Advertisers have always known this. And right now, an entire generation is forming an anti-AI view at exactly the age where those views get locked in. And this isn’t just polling either. It’s gone public and physical. We’ve had graduates booing AI at commencement ceremonies across the country this spring, at one point literally drowning out former Google CEO Eric Schmidt as he tried to tell them to go shape the technology’s future. And then there are the data centers, which is where all this abstract unease turns into a concrete fight. Seven out of ten Americans now oppose having an AI data center built in their area. And that reminds me — I saw in The New York Times just this morning an article that said this community actually wants an AI data center. Like that’s a newsworthy thing now. Community opposition has blocked or delayed something like $64 billion in projects. This is showing up as a talking point in the 2026 midterm elections. And in a handful of disturbing cases, it has tipped over into threats and even violence, with workers on the construction sites of these data centers being assaulted by members of the community. And the resistance isn’t just coming from outsiders. It includes the very employees we’re trying to get to adopt AI inside our organizations — which goes back to our preliminary conversation, Neville. Think about it. If only 16% of the public thinks AI is a net positive, it’s likely that that many, maybe even more, among your employees feel that way. Pew shows usage and approval moving in opposite directions. Half of adults now use these tools, up from a third just two years ago, and a lot of them are using it because their boss told them to use it, while at the same time they distrust it and maybe even despise it. And that’s the gap we have to manage internally. We can talk about the PR challenge AI companies are facing, but let’s talk first about what communicators actually can do about this internally. You have to acknowledge the fear instead of dismissing it. The job-loss anxiety is rational, and pretending otherwise just torches your credibility. We need to separate adoption from advocacy. People can use the tools well without having to love them. We’ve seen this with other tools. I remember — I can’t remember what the tool was that I was using for charts and graphs, this goes way, way back into like the 1990s — but I wanted to use Harvard Graphics, and I was told, “No, our IT department doesn’t support Harvard Graphics.” So we really have to help people understand: look, this is the tool we’re using in the job. You don’t have to love it, you just have to use it. We have to give employees a voice in the rollout rather than just a mandate, because forced use with no input is exactly what breeds resentment. As I mentioned before, I’m on the AI committee where I work, with other frontline employees and non-IT managers and people who are being asked to use it. And we need to lean on trusted peers to carry the message, not executive proclamations, because executive enthusiasm is part of what employees are skeptical about in the first place. As for the AI companies themselves, they’re in damage control right now. They’ve lost the chance to set the agenda. The most striking sign of that is this latest techlash. Tech still polled better than politicians. Today AI polls below every major political candidate, which means the political cost of cracking down on it has basically evaporated. They had a window to set expectations early, honestly, with community buy-in. They missed it. And now they’re negotiating from a deficit. And from where I sit, that’s an argument for startups to embrace PR and communications, because I don’t think any of them really did. If they did, they would have had a PR person telling them that going out there and saying, “This is going to cause massive job loss,” is a really stupid approach to building support for what you’re doing. And yet that’s what they did.

Neville Hobson: It certainly is a muddy picture, it seems to me. I was looking at the Pew report whilst you were talking, and this is a hefty piece of research, I have to say, but a lot of striking contradictions appear to me in trying to understand why this is happening. I mentioned when we were chatting earlier that I don’t see news headlines in the mainstream media in the UK about groundswells of anti-AI sentiment in this country. Not to say there isn’t any, but it’s certainly not driving the news agenda in any way that I could tell. But I found it most interesting — just to break out some snippets from Pew’s research — they say the share of Americans who say they use ChatGPT, which they say is the dominant one of all the chatbots, the one preferred by most people, that usage by Americans has more than doubled since 2023, which is when it became part of public consciousness. Interesting, I think. They report using ChatGPT far more than other chatbots. They say the second most-used platform is Gemini, followed by Copilot and Meta AI. I was surprised at that, because I’ve started using Claude, and that’s way, way down their list, according to Pew. They also talk about — I found this interesting in the context of something else that I mentioned — that Americans are more likely to say, according to Pew, that chatbots help rather than hurt their productivity, knowledge, and creativity. That would explain why more people are using it. But what about the folks who — what about all this anti-AI sentiment that’s emerging? Are they not using this? Are they part of the other percentage that doesn’t? An interesting side explainer, I suppose, to understanding the wider picture about smartwatches, smart home devices, and other things like smart speakers, where you can also use AI. The thing is, though — and clearly I’m not the demographic here, Shel, so this comment is anecdotal —

Shel Holtz: They are using it. Yeah, I’m sure they are.

Neville Hobson: You end up using AI and not realizing you’re using AI. So I’ve taken to using Google’s little widget that they run, the AI mode. 99% of everything I search uses that, unless I’m asking just for a phone number, which is not the kind of thing I normally ask, actually — I don’t phone anyone these days. I often ask questions like, “How many miles is it from A to B?” I often ask that kind of question. And if I use Google’s AI mode, it will ask me, like, “What do you want — kilometers or miles? Direct line, as the bird flies, or roundabout?” I don’t want those questions, right?

Shel Holtz: Yeah. “Freeways, no freeways,” yeah.

Neville Hobson: Exactly. So that’s interesting, all that stuff. A majority of Americans — 60%, so that is a majority — say they read AI summaries at the top of search results. I would imagine that that is growing. Another 10% aren’t sure if they do that or not. Interesting. So Americans predict AI’s impact on society and on them will be more negative than positive. So notwithstanding the majority of people using it, which has doubled since 2023 on ChatGPT, most say the impact on society and them will be more negative than positive. So is that what’s driving the anti-AI sentiment? Younger adults are more wary of the potential impact on society and on them than older groups, yet the younger groups are the ones using it most. So there’s, to me, a paradox there. Roughly two-thirds of Americans say AI is advancing too quickly. So you can now see that you can actually grab some metrics that are the “yes, but” to the “I use it, I’m getting benefit.” Yes, but — so maybe this is about balance. So another metric: most think AI will make their personal information less secure. And there’s that kind of niggle in the back of your mind. Then there’s some political stuff they go into in some detail here. But it got me thinking: maybe you can have this. “This is beneficial, I get what I want out of it, but I hate it.” Maybe that’s what’s going on here. But nevertheless, either way, this is not a good landscape to be gazing at in the context of where AI companies are developing their products. As I mentioned, I’ll be using Claude a lot in my migration experiment. I use Claude and ChatGPT interchangeably. I’ve got too much invested in ChatGPT just to give it up. And in fact, some of the stuff I ask ChatGPT to do, particularly if it’s summarizing something, I quite like what it provides — sometimes better than Claude. Sometimes I do both: give me this, and I give the same prompt to the other one. Projects and those kinds of things in Claude I’m not using as much as I thought I would. So the point, though, is that maybe there is, Shel — you can embrace two different perspectives at the same time. “I get benefit from this, it helps me do what I’m doing. I don’t trust it. I hate what it’s doing to society, and so I’m anti-AI, but I find it useful.” Is that what’s happening?

Shel Holtz: I think so. I think there are a lot of employees who recognize that if they want to be employed in five years, they’re going to have to know how to use this. And they’ve —

Neville Hobson: Yeah, but this is not just about employees. This is people generally in society.

Shel Holtz: Sure. Yeah. I think there are people who are getting benefit from it, better than they can from other tools, and they recognize that, and they still distrust it. They still don’t want the data center in their backyard. I know people who don’t use it at all. And one of the reasons among some of those people is that they think the whole thing is based on theft. I even saw this as a post on LinkedIn — some discussion of AI, and one person left a one-line response saying, “All AI is theft.” I was very tempted to leave a comment saying, “You’re talking about generative AI, there are other kinds of AI.” But the notion that it’s all based on scooping up everything that’s on the internet that people created, and they weren’t asked and they weren’t compensated — you know, Bernie Sanders, I think, has a proposal that there be a sovereign wealth fund where some of the profits from AI go into that fund and are used to benefit people, because it’s their content, it’s their intellectual property that is fueling all of this generative AI.

Neville Hobson: But it seems to me, though, that those kinds of big-picture statements don’t have any impact on people. I hear that argument a lot. “AI is theft, it scrapes content” — which it does, hence all the talk, particularly here in Europe broadly and here in the UK in particular, on permissions and the new regulations that they’re bringing in that are related to copyright and intellectual property ownership. Good luck with all of it, I say, because these are geographically based laws, and we’re not talking about geographically based protections. So I don’t know how on earth they’re going to solve that. I’m not sure that they can. In which case we’ve got something, have we not, that is almost an impossibility: that if this continues like this — and to your point you mentioned earlier, and I have seen reporting of that here too, of very strong anti-behaviors, including violence — that we see an increase in that. Data centers here don’t seem to be a prominent topic of debate; i.e., it’s not like dozens of them are sprouting up all over the place. It’s not like I read recently in the US, there’s this town somewhere in Oklahoma, I believe — might have been Texas — where the town’s council that runs the town, it’s about 2,000 people in this little town, agreed to the investment program of a company who wants to build a data center there. And to do that, they’re going to need to build, including the infrastructure for energy generation, that would serve a city the size of Chicago. So the whole nature of the whole living environment is utterly changed if they go ahead with this. So —

Shel Holtz: Are you suggesting that more than 2,000 people live in Chicago?

Neville Hobson: Just a few more. So I get the logic of that, but it seems to me that there doesn’t seem to be any strong desire at government levels, whether national or local, to seriously address people’s concerns here. And there you have the paradox, because, “Yes, I love what I can do with this AI tool, it’s wonderful, but I hate it. I don’t want it building a data center in my town, but I want the benefits of using this AI.” Is it what we call in the UK NIMBYism? You’ve heard of the acronym?

Shel Holtz: Yeah, “not in my backyard.” Certainly.

Neville Hobson: Right, but I don’t mean to belittle people who do. It’s not all just that. There is some of that, clearly. But these are genuine concerns people have.

Shel Holtz: Well, I mean, in this instance, where you don’t want it in your backyard, it’s because it’s going to drain your water. There are places where data centers have been built where you turn on the tap and it trickles, because all the water’s going into the data center, and electricity rates are rising because of the consumption of the data centers. I think the companies that are building and running and operating these really need to make the investment in energy infrastructure so that they are actually contributing something rather than taking it away. By the way, I looked it up: KPMG did research. In the UK, 42% of adults are willing to trust AI, so the majority does not. 57% are willing to accept or approve AI use, meaning nearly half remain hesitant. 78% are concerned about negative outcomes from AI, and 72% are unsure whether online content can be trusted because it may be AI-generated. 80% believe AI regulation is required, and 91% want laws to combat AI-generated misinformation, and only 29% trust the UK government to use AI for its tasks. So that’s —

Neville Hobson: Well, addressing the issues — that’s the 91% who want that happening — that’s in train, as it were. But I get a little cynical about some of these surveys, particularly where you’ve got such huge numbers that you then say, “Therefore the majority of people don’t support this or do support this,” or whatever. I want to know how many of the “don’t knows” or didn’t respond or whatever. But either way, it’s a hot-potato topic, more so in the US than here, that’s a fact, because you’ve got situations happening that aren’t happening here yet, particularly related to data centers. There’s not dozens of them springing up everywhere. Hey, we’ve got a nuclear power station being built further north of here, but that’s not quite the same thing, right? So I don’t believe there’s a way to solve this cleanly that will keep everyone happy. Like most things in politics, you can’t please everyone. But this in the US certainly, according to all this research, is a growing issue.

Shel Holtz: I think the frontier labs — OpenAI and Anthropic and Google — certainly need to put their heads together on a strategy to turn this around. This can’t be something that they just shove into the background. The frontier labs are going to have to get together and really figure this out. I know they’re trying, because I’ve seen the $400,000 salaries for storytellers, which is a cute, very precious way of saying they need good PR. And we need better communication, and stronger strategic planning in our organizations. This is a perfect storm that has to happen, and I don’t know how it will, but I’m sure we’ll be talking about this in the future.

Neville Hobson: Yep, I’m sure too. So let’s move along and talk about the decline of trust in news. Trust is one of those words that gets used so often in discussions about media and communication that it can start to feel abstract. But every year the Reuters Institute for the Study of Journalism at Oxford puts a very concrete number on it. And every year for the past several years, that number has been going in the wrong direction. The Reuters Institute Digital News Report is now in its fifteenth year. It covers 48 markets and draws on responses from around 97,000 people worldwide, which makes it one of the most comprehensive ongoing studies of news consumption habits anywhere in the world. We’ve referred to its findings many times over the years on For Immediate Release, and it remains, in my view, the essential annual benchmark for anyone working in or around journalism, communication, or media. The 2026 edition was published just recently, and I want to focus on one finding in particular — not because it’s the only important one, and we may well return to other threads from this report in future episodes, but because it captures something important about the environment in which all of us as communicators are now operating. Global public trust in news has hit a new low, says Reuters. Just 37% of people worldwide say they trust most news most of the time. That’s down three points from last year. Falls were recorded in 29 of the 48 markets surveyed. In the United States, the figure has dropped to 25%. Among right-leaning Americans, it’s 15% — the lowest figure recorded for any demographic in any country in the entire 15-year history of the survey. In the UK, where I’m based, the picture is also stark. Trust has fallen five points this year, to 30%. But here’s the figure that really stopped me: that’s 20 points lower than it was ten years ago. Twenty points in a decade. That’s not a dip. That’s a structural collapse in the relationship between news organizations and their audiences. And it’s not as though people have stopped caring about news or stopped believing in what journalism should be. The same report finds that 48% of people globally still say they prefer news with no particular point of view — an endorsement of impartiality as an ideal that has barely shifted in years. People still believe in what journalism could and should be. They just stopped believing that’s what they’re getting. So when trust has fallen this far, this consistently, across this many markets, is there a realistic path back? Or have we crossed a threshold where declining trust in news is simply the permanent condition of the information environment we now inhabit? Shel?

Shel Holtz: I think it’s not something that’s going to be solved easily, if ever. The fact that right-leaning Americans distrust news more than centrist or left is consistent with the data that we talked about on the last weekly episode, when we talked about — I mean, the episode was about misinformation, or actually disinformation, and media bias. But the media bias effect that we talked about in that episode, that has been around as a measured phenomenon since the 1980s and has been reaffirmed with research ever since then, is at play here, because it finds that right-leaning Americans are more inclined to believe that media reports are biased against them than centrist and left-leaning. Now, centrist and left-leaning also believe that media reports are biased against them, just not to the same degree. So this is that. This is people getting into their bubbles, feeling that media bias effect, and not trusting the media. I think you see a lot of reporters, journalists, leaving the outlets they work for and starting their own media companies, starting Substacks, because they as individuals find that they are trusted; it’s the outlet that they work for that isn’t. So we’re seeing a shift in where journalism comes from. And when you talk about this shift toward social media being the source of news for people, a lot of that is journalists who have started media operations that present their content through social media. The other thing that I find interesting is that 70% of adults in the US say they have a lot or some trust in information from local news organizations. That’s way higher than those who say they trust the national organizations. Republicans trust local news more than national — 64% trust it more. So it seems to me that — I mean, we could speculate about what news media organizations, the New York Timeses of the world, the Washington Posts of the world, the CNNs and NBCs of the world, what they can do about it, but that’s really outside our area of expertise, isn’t it? What do communicators do about this if they’re trying to get news coverage in outlets that people don’t trust? I think the first thing to do is start looking at those local news organizations. And you know that there’s been a serious decline in local news because of the internet and because of social media. I think business needs to invest in local news. I don’t know that you want to go as far as what Alabama Power did — we’ve reported about that on FIR. They actually created a local news outlet that they maintain is independent and unbiased, but it definitely skews toward the topics that are relevant to them. But I think we need to find a way for the business world to help bring local news back. And I think there are other ways that this can happen. I’ll tell you, I set up a Claude Skill, because there is no local news where I live in Concord, California. There’s something in the next community over, it’s called the Clayton Pioneer. It is absolutely awful. You don’t find out what the city council did, or the zoning commission, or the school board. It’s all puff. So what I did was I set up a skill, and it goes out and it checks the minutes of the last city council meeting and the zoning commission and the planning board and all of these agencies in the city, and it builds a newspaper. It’s just for me at this point. And every day I get — it’s like five pages, in a PDF. It also talks about where streets are going to be closed and stuff people actually need to know. I keep tweaking it, but when I get it where I want it, I’m going to buy a domain and I’m going to have this skill publish it as HTML to the web, so that there is an outlet. And I’m going to get out there on Nextdoor and other platforms and let people know it’s there. It’s not a place where opinion is shared. This isn’t puff. You want to know what the school board decided? You want to know what the zoning commission approved? This is where you’re going to find that, in addition to today’s weather and street closures and the police blotter and things like that. But this is where I think businesses need to start building relationships with reporters — in the local news media, because that’s what’s trusted. The other is that they need to do the owned stuff and start doing that external-focused journalism. Not press releases, but journalism.

Neville Hobson: Yeah. There doesn’t seem to be a huge groundswell of interest in doing any of those things, though, I would say. But I found it interesting that this whole trust paradox is not resolved at all. So audiences say they endorse impartiality as an ideal. And that makes complete sense to me, particularly your point, which I agree with. You’re talking about journalists starting Substack newsletters and all that kind of business. I see it not just that — I see it more as, who do we trust? We don’t trust an algorithm to create news, do we? We trust a journalist writing the news. And that plays very clearly to your point about people connecting with a journalist much more than the medium they’re writing for. So hence many people have moved on from the employment in the newspaper to running their own newsletter, some people making money at it, doing quite well. I think the Reuters report also mentions something: 48% globally say they prefer news without a point of view. I agree, I’m in that group, I have to tell you. I don’t want editorialized news. I do not want to read news that’s dressed up as news, and it’s not, it’s an opinion piece. You see that a lot, particularly online. Here in the UK, we’ve got a move in regional newspapers up and down the country, many of which are owned by large monolithic organizations, that publish AI-generated content as their news stories. And we’ve talked about this before. A lot of it is the sports reports, for instance, but just generally local news. And I’d be amazed if they have a sustainable business model. Or could it be that people don’t actually care, because it’s gone beyond — “I can’t do anything about this, I don’t see any change, therefore I don’t care anymore,” so they’re looking at other places to get the news from? And therein is a paradox of your idea of doing what you proposed — creating news content. That, to me, is a smart way of doing it. Your example of the Alabama Power Company, I think, wouldn’t meet the impartiality test, no matter how good they say their content is. And I think there is the problem, then, with businesses trying to do deals or trying to cozy up to journalists: you need to have genuine impartiality. So there’s probably few business models in that mix there, I would say. But in the small town where I live, there’s only 9,000 people here, so it’s actually quite a large town by UK standards. Local media is pretty good online. There are a number of reporters I like, particularly the ones who talk about things like you mentioned — planning applications, roadworks and diversions, all that stuff. It’s good, it’s up to date, and they’re using Facebook mostly, and there are lots of groups that you can join to follow this. But that’s all individual actions and a couple of local newspapers. There’s nothing scalable in that at all. So I don’t know where this actually happens, Shel. I don’t see — people haven’t given up on what journalism should be. They probably don’t even think about the word “journalism” in all of this. They just want impartiality in their news reporting. They’ve given up on it. Is that fixable, do you think? Is there a fixable gap here?

Shel Holtz: I’m sure there is, but I don’t know what it is for the news media. I just have to think about what communicators do to get their news out in this environment. That’s what concerns me. And I think a number of things we need to do. One — it’s interesting that Cision and the companies that do the press release distribution and the contact with the reporters, they all know the reporters that work for the mainstream news outlets. Do they have the Substacks from professional journalists, or the Ghosts, or whatever service they’re using? I don’t think so. I think somebody might be able to make some money by offering a service that does what Cision does, but with those independent journalistic enterprises. But I think as communicators, we need to find the journalists who are doing that and have big followings, and start to build relationships with them, just like we have been with those who work for the newspapers and the TV news. We need to find the podcasts. Increasingly we find — and we’ve talked about this on FIR — that the interviews on podcasts make news. You want to get the word out, get on a podcast that is influential in your industry or whatever your area of subject matter expertise is that you’re dealing with. But we need to move where the trust is. And getting your news out through outlets that people don’t trust, I think, is not a viable solution. But it’s what we’re accustomed to, and it’s what agencies get paid to do. And it’s a shift that I think will be very, very slow, but we have to start.

Dan York: Greetings, Shel and Neville, and everyone of our listeners all around the world. It’s Dan, coming at you on a gorgeous sunny day, the first Saturday without rain in Shelburne, Vermont, for quite a while. So we’re enjoying it. But right now I want to talk about Mastodon, and specifically about collections and helping people get started with finding accounts to follow. This has always been a challenge, right? When you start up with a new service, you go in there, and who do you follow? What’s your feed doing? Now, Mastodon has had for a while a thing with some recommended accounts that you could follow, but those were ones that Mastodon, the central entity, put together, and they were looking for a way to do something broader. In the meantime, of course, Bluesky came out with what they called starter packs, where anybody could create a starter pack full of people of a certain topic, whatever else, and you could then discover one of these starter packs, and you could follow everybody. You’d be able to get on there and see that, and boom, your feed suddenly is full of a lot of different activity and things that were there. So people in the Fediverse were looking at what Bluesky did to make it easy, and there were several different experiments people have tried. There are actually some people calling something starter packs. There are some other people trying other different ways to go and do it. But there wasn’t something quite from the central Mastodon company until this latest 4.6 release, where it has created these collections. Now, it’s actually interesting. It’s kind of the beginning of the journey, because with this release, what they did was they made it easy to create collections. You can create them, you can have a link to share, but there’s not as much about finding them, and the rationale makes sense. They said, you know, before we can really get a lot of search and discovery working, we need to have collections. So this release, 4.6, was all about getting the mechanism to create collections out there, and then in subsequent releases, they will work on making them more searchable and discoverable, so that they could replace, for instance, the recommended accounts that Mastodon has when you first join. Now, there are a couple of interesting aspects. One criticism of Bluesky’s starter packs was that your Bluesky account could be added to one without permission. So if I wanted to create a starter pack of people I don’t like, for instance — I don’t know why you would do that, but I could. I could add accounts to something, and if you didn’t feel comfortable being part of that, maybe you don’t want to be there. There wasn’t a great mechanism when Bluesky first came out with that. So collections brings that in in a big way. When you go and add people to an account, first of all, they have to have turned on — or not turned off — a switch in the settings which allows them to be used in search and discovery. So that’s one way: if you just don’t want to be in anybody’s collections, you can turn that off, and then people will have no ability to add you to any of these kinds of collections. Now, the other aspect is, when you are added to a collection, you get a notice that you have been added, so that you can choose to remove yourself from a collection if you want to. And at any point in time, if you find that you don’t want to be part of that collection, you can go and remove yourself. So it’s a much more consent-based thing. And also, in this initial phase, they are not putting a “follow all” button. So there’s no way to just go and click on “follow all” and do it. You just have to go down through the collection and click, click, click, click — follow the people that you want to. Other note: it’s right now restricted to only 25 accounts, not the 150 that were in Bluesky starter packs. And again, partly it’s to learn and to see what was there. They found one of the criticisms of some of the Bluesky starter packs was that they became stale, with too many dead accounts. So this is partly a forcing factor to go and see what’s there, and they want to learn, and that may change over time, and we’ll have to go and take a look at what happens. But it’s very interesting. I’ve created a couple of collections. One added factor here is that Mastodon is a collection of thousands, tens of thousands, of servers, each one of which has to be running the 4.6 software for the accounts to be on it. So I could add Neville, because he was on a system that was upgraded. I couldn’t add Kjell, because the system he’s on is not upgraded. So there’s a factor here that will take some time for this to be able to work with. But it’s an interesting way to go about how do you do this form of discovery and how to work with it. So it’s called collections. If you go to my account on mastodon.social, Dan York, you’ll actually see on my profile page now there’s a link to where these collections are, and you can see them. I have kept mine public. There’s also, of course, a feature to make them unlisted so that people couldn’t find them. But it’s something interesting, something new to try, and we’ll see how this helps with the further adoption of the Fediverse and Mastodon. Speaking of Fediverse and Mastodon and other stuff, I want to just tell you that there’s a woman out there named Elena Rossini — she’s from Italy, but living in Paris — who’s been writing some amazing articles right now about the service called W Social. It was launched to great fanfare at the Davos meeting, where all sorts of folks are, and what’s happened in the past several weeks or so is that the accounts from Bluesky of the European Commission, its president, Ursula von der Leyen, the European Central Bank, and other different people have moved from Bluesky over to these W Social servers. There’s a lot more than I can talk about in the scope of this report, but to say that it’s a very curious thing, because the people announced this, then they seem to have seized on using Bluesky, the AT Protocol, that piece of that. They’ve launched their service. They’ve then moved their code to be closed-source, and they’re just doing a bunch of different kinds of sketchy things. They’re promoting it as a social network that will require age authentication, age verification, age assurance — I’m not sure even which term they’re using — but you have to prove your identity or provide a government ID to show your age, and they’re working with another entity called W Identity to create this. There’s a lot of splash, a lot of fanfare, but it’s turning out they haven’t actually been talking to people in the “atmosphere,” as it’s called, the set of people working with the AT Protocol. So I would encourage people to read the articles from Elena Rossini, and to think about what is really going on here, and is this actually something that will provide a true, decentralized, open service for the Europeans, or is this somebody else trying to create a centralized service that happens to be Europe-based? Not clear yet. Lot of unanswered questions in all of this. I’m going to leave it there, send it back to you guys. Back to you, Shel and Neville. Thanks for listening. Bye for now.

Neville Hobson: Thanks for the report, Dan. We’ve not had a chance to listen to it, but I’m very interested to hear what you have to say with regard to W Social, because that is something I’ve been paying attention to. I signed up for it way back, some months ago now, when they first announced they were coming. I’m still on the wait list. But I’ve seen a number of reports literally raising cautionary notes about this, along the lines of what you’ve included from Elena Rossini, for instance. A really good website, by the way, I would say. So I haven’t read her report yet, but I’m keen to listen to what you have to say about this. So I’ll be doing that once we’ve published the recording.

Shel Holtz: Me too, Dan. I got home at, what, about one o’clock this morning, and I barely made it to the scheduled start of this recording. So I’ll be listening to you a little bit later. Always look forward to it, though. There is a shift going on. I suspect a lot of our listeners are living through this, whether they’ve put a label on it or not. And I read about this most recently — it’s something I’ve been aware of, but I just read this piece by Geetikka Bangia, who heads PR and corporate comms for Stryker in India. The oldest rule in our profession has flipped. Think back 20 years. The best PR people were the ones you never heard about, unless it was through a professional association, right? The Gold Quill Awards or the Silver Anvil Awards, that type of thing. They were invisible, but they were essential. We built the brands for everyone else — the CEO, the company, the product. That’s what we wanted to shine a light on, and we stayed in the shadows. That was the job of PR. In fact, if PR made the news, it meant something went wrong. Well, according to Geetikka, that rule is now dead. Today the most effective communicators are the ones publishing thought leadership on LinkedIn, speaking at conferences outside of the industry, putting their insights out in public. Her line — and I love this, because it’s pretty blunt — is, if you’re still operating like it’s 2005, “brilliant but invisible,” you’re playing a game that no longer exists. Your personal brand, she says, isn’t vanity, the way the industry used to see it. Today, it’s survival. So what changed? Social media, and LinkedIn in particular, democratized visibility. Suddenly junior people were building audiences, mid-level communicators were publishing, and employers noticed. Trust is in play here. Edelman’s data keeps showing that peers now outrank CEOs in credibility, which means your own authentic, consistent voice can actually enhance your employer’s brand — or, if you get it wrong, you can certainly damage the brand. When Bangia looks at the people who do this well, there’s a clear pattern. They add value beyond their job description. They share insights. They don’t promote themselves. They build trust. They’re not looking to build follower counts. Her example is Parag Agrawal, who built a reputation as a genuine tech thought leader with educational posts long before he became the CEO of Twitter. So his personal brand signaled expertise, not ambition. But again — and this is where it gets interesting — she’s very honest about the dark side. The line between personal opinion and professional representation is thinner than we think. And in PR, where we manage reputation for a living, our own missteps get magnified. You know the Weber Shandwick stat that nearly half a company’s reputation is attributed to its CEO? She extends that logic right down to the individual communicator. If you’re credible, your employer benefits. If you’re controversial, they pay the price. She says she’s watched comms professionals torch their employer’s reputation with a poorly timed political post — personal brand is damaged, employer brand becomes collateral damage. So we need to figure out how to navigate this. And she offers what she calls a Goldilocks zone, right? Not too much, not too little. She has four rules. Be visible but purposeful — don’t post to post. Stay opinionated but professional — you can hold strong views without being divisive. Build your brand, not your ego — be known for something valuable, like crisis management or storytelling, not just chasing virality. And this is the one I’d underline: know when to stay silent. Know when to shut up. Not every trending topic needs your take. PR people, of all people, should understand message discipline. Her bottom line is, the question isn’t whether to build your personal brand anymore, it’s how — with intention, integrity, and the understanding that in our field, your reputation isn’t just yours, it’s intertwined with everyone you represent. And the thing I want us to think about is the organizational flip side of all this, because if every employee is now a brand voice, then our job isn’t just building our own visibility, it’s helping the whole organization navigate theirs.

Neville Hobson: Yeah. I remember the days — I’m sure you do, Shel — when anything anyone wanted to say about the company externally was not allowed at all. It had to go through official spokespeople. And in fact, it was a disciplinary offense if you uttered something that was quoted in the newspaper, for instance, without permission. Imagine that today still. Imagine if that was still the case today. But the landscape is utterly different to what it was in the 90s, never mind the 2000s. What Geetikka talks about is the visibility thing first, that struck me. Because back in those days, none of these platforms, none of these tools, none of these channels existed. So there was limited means by which you could talk publicly about something and attract attention to you as the person saying these things. Things changed when blogs hit the scene back in the early 2000s, where suddenly anyone could be a publisher. And we relished those times, didn’t we? We wanted everyone to be doing this. We got our wish, so we had good stuff and bad stuff. But I can’t imagine this changing. If anything, it’s going to become more microscopic, in the sense of, you are under a microscope all the time. And hence her advice, Geetikka’s counsel in this really good post, is that you need to be cognizant, very, very aware, of literally everything you do and say online. And the thing that never ceases to amaze me, Shel, is the people in responsible positions, with authoritative opinions and presences, who don’t do that. It amazes me — where someone who’s a CEO of a company, or a senior politician of some type, says something, gets all over the tabloids in particular, and that’s it, your reputation’s toast. And before you know it, after a few months, that person’s gone, probably. But there is damage. And in fact, Philip Bourne has talked about this quite a bit too, the damage resulting from loose lips, if you like. So it is something to pay attention to. And I like the way she says that personal branding isn’t about becoming an influencer — heaven forbid — it’s about being known for something valuable. I utterly agree with that. And I think, if some of the people I know who were journalists or reporters on a national newspaper of some type, or were senior people in organizations who are now gone independent themselves, who retain the credibility they’ve earned from their previous experiences and roles —

Shel Holtz: A lane for that, right?

Neville Hobson: Right, exactly right. That’s carried forward to what they’re currently doing, because they are still trusted by people. So their reputation hasn’t changed, because they haven’t changed the consistency of how they walk the talk of their brand, if you will, as a means to talk about their client or their employer. So it makes common sense to me, much of this. Yet I am constantly surprised when I see examples of common nonsense being spouted, where, you know, “What were they thinking?” I say to myself every time I see it. So “know when to stay silent” is a very good one. And there are far too many people with verbal diarrhea, it seems to me, who have an opinion on everything and they will spout it. And I see that myself, particularly on LinkedIn, as literally, “Look at me, look at me, I’ve got these things to say, and it’s great, and I know all these topics.” That’s what I’m seeing. So that’s our landscape, Shel.

Shel Holtz: Well, yeah. And there are figures circulating out there that something like 70% of employers now consider a personal brand more important than a resume. And even LinkedIn has researched that people with active personal brands see nearly 50% more inbound opportunities than those without. So this is something that you want to do. And the other thing is that, as other employees in the organization and other parts of it are doing this, this is something to coordinate. We’ve got a guy who does an occasional post, maybe monthly. He’s out on one of our most important projects, and he does these great posts about milestones they’ve reached and what it took to do it. We end up sharing it through our advocacy platform. Now, what if other employees were doing that? The advocacy platform is one thing — it gives employees our content to share in their communities. But I’d love to see some of our subject matter experts, the people who really understand concrete, become — their personal brand in social media is now concrete, that sort of thing. And then we can coordinate that, and we can leverage all that as PR opportunities, and then we can share that in the advocacy tool for other employees to amplify. If people are doing this, communicators need to get their arms around it, not just manage their own personal brand.

Neville Hobson: They get known for it. They get known for it. Yeah, lots to learn from this, I’d say, Shel. Okay, so sound advice, very nice article. Now let’s talk about a reputation crisis — a PR crisis, but a reputation one. And this is something quite extraordinary that I want to share here. Sometimes a single incident cuts through the noise and forces a conversation that the industry probably would have been having for a while. Recently, a week or so back, that incident involved a UK discount voucher website called Wowcher, a three-year-old boy, and a crocodile enclosure in a zoo. Let me give you the background, because if you’re not based in the UK, you may not have followed this disturbing story, although I have seen it talked about in media around the world, actually.

Shel Holtz: I read this on CNN and The New York Times, so this has made the rounds.

Neville Hobson: Right, yeah. So on Thursday, the 18th of June, so not long ago, a toddler three years old was pushed by a stranger into an enclosure containing Nile and saltwater crocodiles at a zoo in Huntingdonshire in England. The child suffered serious injuries and was taken to hospital in Cambridge, where he remains in a critical but stable condition. It’s a deeply distressing story. A family’s worst nightmare played out in public, and a news event that dominated the UK media cycle for days. It gets worse, Shel. It really gets worse. Two days later, on the Saturday, just two days on, Wowcher sent a marketing email to its customer distribution list — so we’re probably looking at tens, if not hundreds of thousands of people on that list. The subject line of the email read: “Snap up these deals quicker than a croc can catch a kid!” Exclamation mark. Well, as you can imagine, the reaction was immediate, universal, and unsparing. Marketing professionals, commentators, and members of the public condemned it without reservation. There was no debate about —

Shel Holtz: Russell Brand thought it was hysterical.

Neville Hobson: We don’t talk about Russell Brand, sorry. There was no debate about whether it was misjudged. There was no defense offered from any quarter. Just about all mainstream media in the UK, including the dozens of regional press outlets, covered the story. It featured in the news podcasts and across social media. LinkedIn lit up. Email marketing specialist Beth O’Malley, whose post on the subject drew widespread engagement, described it as reflecting a wider problem: that the drive to get the open, to get the click, to make the metrics go up, has overtaken something more fundamental. As one commenter put it simply, whoever was involved in creating and sending that email forgot that there are real human beings on the receiving end. Wowcher issued an unreserved apology. They described the wording as unacceptable, said it should never have been written and was never approved for use, and committed to urgently reviewing and strengthening their creative approval and sign-off processes. Which, of course, raises the obvious question: if it was never approved, how did it reach what is presumably a very large mailing list? We don’t know the full answer to that yet. There has been speculation that AI may have been involved in generating the content, and that’s possible. But I want to be clear about something. Whether a human wrote those words, or an AI generated them and a human failed to catch them, the root cause is the same. It’s a failure of humanity. You hear this word “humanity” applied a lot, but it’s a real word, and it’s worth paying attention to. A failure of empathy. A failure to pause for even a moment and ask the most basic of questions: how would the family of that little boy feel if they opened their inbox and read this? That’s not an AI problem. That’s a people problem. And it sits at the heart of a broader crisis in email marketing culture, one where the relentless pressure to perform, to stand out, to optimize for attention, has gradually crowded out the human judgment that should be the last line of defense, if not the first. So here’s the question I have. In a world where content is created faster than ever, approved under pressure, and distributed at scale, who is actually responsible for ensuring that basic humanity remains in the loop? And what does it take for an organization to lose sight of that so utterly completely?

Shel Holtz: It’s unbelievable. Just staggering. I have no problem with newsjacking — this is the term that David Meerman Scott coined. He wrote a book about it. He had great examples of it. I even have a Claude Cowork skill set up that runs at 4 a.m. every Monday morning to scour the news for stories that I can leverage and write on their coattails. I haven’t found one yet that I’d actually want to use, but it’s giving me some interesting stuff, and I’m convinced that one of these days it will. I’m tweaking it every now and then based on the results I see. I am a fan of newsjacking, but for God’s sake, use your head before you go with one of these things. Was the wording clever? Yeah. It was also insensitive and inhuman and horrible. I don’t know what else to say about this. I will comment, though, on the apology. I love the fact that it was an unreserved apology. They were unequivocal in their condemnation of it. But I think they needed to end the apology by saying, “We will report on the steps that we are taking in order to ensure that this doesn’t happen again, and we will continue to report on what we learn about how this happened,” and then follow up on that. Just to leave it to say “we’re going to change our procedures” is woefully inadequate. I think people need to know that you’re actually taking the steps that you say you will. The trust gap is huge here. After you have done something like that, just to say, “We’re sorry, we’re fixing it,” is not enough.

Neville Hobson: Yet it looks like people are willing to accept that. So, I mean, this is a business that is hugely successful. They do really imaginative, creative TV advertising campaigns. And the play on the name Wowcher, you know, “voucher” with a “wow” — I mean, it’s smart, it’s very clever.

Shel Holtz: Sure. Well, it’s like Groupon — “group” and “coupon,” right?

Neville Hobson: Yeah, very clever. Yet — what bothers me, I think, is, are we as a society — you know, condemnation was universal, people expressed horror at what they did, all that, and the poor little boy was savaged by crocodiles — yeah, they’re still buying stuff from Wowcher. They’re still doing business with Wowcher.

Shel Holtz: No boycotts, huh?

Neville Hobson: I’m not suggesting, for instance, that they shouldn’t be doing all those things. But isn’t what happened so grotesque that you’d think it would stimulate people to be, “That’s it, I’m not doing anything more with this company”? And the campaigns online — I’ve not seen anything like that. So what does that tell us about our society, is my kind of rhetorical question, I expect. But I think the point that Beth O’Malley raises — that this reflects a culture in email marketing where anything that drives opens and clicks is tacitly approved — is worth looking at. Is this a Wowcher problem? Or is it symptomatic of how the entire performance-metrics model of email marketing has just normalized a race to the bottom in judgment and taste? What do you think?

Shel Holtz: I think you’re looking at two sides of this issue. The first is the creation side, where all of what Beth O’Malley talks about comes into play. And yeah, I think she’s right. I think the drive for clicks is overwhelming the application of judgment and common sense. The other side is the reaction, where people are horrified for 15 minutes and then they continue to use the product. They’re not boycotting. It’s not a revocation of their license to operate. So I think on the societal side of this, I wholly agree. I think we tolerate a lot more these days. We tolerate corruption in government a lot more these days. I mean, Vice President J.D. Vance was on some show — this happened while I was traveling, so I just read it in passing — but basically he said, if what Richard Nixon did that cost him his presidency happened today, it wouldn’t last in the news cycle for 15 minutes. And I’ve read news outlets say, you know, he’s probably right. It’s not that what he did wasn’t illegal and probably should have ended his presidency. It’s just that today people would have shrugged and gone, “Yeah, just business as usual. Those marketing guys, they’re terrible, but I love their product.” So yeah, I think the bar has been lowered considerably for what we’re willing to — I mean, outrage is everywhere, so I’m reluctant to say “outraged about” — but what we’re willing to act on, that bar has dropped precipitously, I think.

Neville Hobson: ‘Tis.

Shel Holtz: Yep. Let’s move on to our final report, which is really fascinating, because there are two studies that have reached entirely different conclusions. And I have to say, this casts any study that I look at into doubt when I see this. So let’s take a look at these, because they’re both studies that would be of interest to anybody engaged in internal comms. A Fresh Intranet Employee Attention Recession report, which came out in May, found that just 12% of employees read internal communications in full. That’s 12%. The other 88% are skimming, filtering, and ignoring it unless a manager flags it, or they’re handing it to an AI tool and reading the summary instead — at the same time that they’re saying, “I don’t like AI.” Now, here’s the part that makes that number really uncomfortable: 91% of those same employees say the communications feel relevant to them, always or most of the time. So this isn’t disengagement. These are people who want to engage, who say the content speaks to them, but the sheer volume has made reading the whole thing an unsustainable act. Mike Klein, writing this up for Strategic — a great magazine, if you’re not reading Strategic, you probably should — points to the cause. The single biggest factor in whether someone reads a message in full isn’t the subject, the sender, or the format. It’s the cumulative weight of how many other messages arrive before it. And the internal communications index backs this up. Most employees now have ten minutes or fewer per day for internal comms. The most common answer is five minutes, and that window’s been shrinking every year since 2023. Now, here’s the twist on this, and it’s why I wanted to pair these. A second study, from Corbett and Reworked, which Chuck Gose’s ICology was involved with, found almost the opposite. Half of workers say the volume of messages they get is about right, and yet 44% still tune out. Chuck Gose’s read on this is the scarier one. This isn’t overwhelm, it’s passive disengagement. And when employees stop noticing that they’re overwhelmed, your satisfaction scores start lying to you. 89% of workers are only moderately confident that they’re not missing something important. So, which is it? Too much volume, or something else? And I think the answer is both, and they’re not actually in conflict. Volume genuinely destroys attention, but cutting volume alone won’t fix a tune-out that’s really about relevance and trust. Because when you dig into what makes people actually pay attention, it’s specific. 57% engage when a message is timely or urgent. 56% when there’s a clear action required. What makes them tune out is repetition. And I think that’s important, because a lot of communicators operate under that formula that says you have to tell people something seven times before it sticks. They also tune out because of vagueness, and content that could have been sent to anyone. There’s a brilliant one-line test in the report: before you hit send, you should be able to finish the sentence, “After reading this, employees will ___.” If you can’t fill in that blank, the message isn’t ready. And the finding that crosses every one of these studies is about who’s talking. 73% of workers say the sender is the number one factor in whether they trust a message. “From the leadership team” doesn’t cut it. People trust people, not titles. Which leads straight to the manager gap. Across all of these reports, managers are the most trusted, most critical link in the chain, and the most under-supported. 87% of comms pros call manager capability their single biggest risk, and fewer than one in four organizations actually give managers a toolkit. And there’s one more thing I want us to really pay attention to: Mike Klein’s argument that we’re measuring the wrong thing entirely. 70% of comms teams are still tracking opens, clicks, and page views. Only 12% measure anything close to business impact. As Mike puts it, reach without understanding isn’t communication, it’s noise. So the question he leaves hanging, and I’ll leave it here with you, Neville, is whether the profession responds to all of this by refining its content or finally changing what it measures.

Neville Hobson: That last option — changing what it measures — is the one that interests me, because AMEC is a big proponent of, let me call it, proper measurement. Opens and clicks don’t cut it, the same way how many impressions something has got — eyeballs. It’s like, I don’t care how many eyeballs saw the content. I want to know what they did when they saw the content. Did they just move on? Did they click something? What did they do?

Shel Holtz: Yeah, outcomes-based.

Neville Hobson: So I think it’s most interesting. And reading about the other survey that you mentioned that was in the other publication you shared, ICology, that had some interesting findings in there too that struck me as worth attention. You mentioned one: direct managers are the missing link most organizations keep overlooking. Employees trust their manager more than anyone else — yeah, absolutely. But I found this one interesting, the shadow comms finding. That’ll resonate, if you listened to the story earlier, with anyone who’s worked in internal comms. They’ll recognize it immediately: when official channels fail, employees don’t stop getting information. They just go somewhere else — Slack DMs, WhatsApp groups, text messages, hallway conversations, all of those things. So that’s shadow comms. That’s a good way of describing it. Not approved channels. But it has ever been thus, hasn’t it, Shel, for goodness’ sake? It’s not new. The tools and the means have shifted over time, but this has always been the case. You’re going to find other ways of finding out what Harry down the hall thinks about something and share your thoughts with him. And now you’ll do it on WhatsApp. Before, you might mosey down to his cubicle and surreptitiously chat with him. Look, if you haven’t seen the show The Office —

Shel Holtz: About the —

Neville Hobson: — but it’s nothing new in all of this. And yet we still don’t seem to be addressing these things. I wonder why that could be. Could it be it requires some big changes to happen in how you act as a manager, how the leaders behave, and so forth, and indeed how regular employees themselves behave? That’s a leadership issue, it seems to me, first and foremost. So there’s plenty to digest in both these stories. Mike Klein’s piece is a good one, I agree with you. And I think “not measuring the wrong things” is excellent. And Richard Bagnall at AMEC would have some views on that, I’m sure. Are we measuring the wrong things? So plenty to take away from this show.

Shel Holtz: Yeah, absolutely. And the shadow communications has always been real, and more so now that there are digital tools that enable it. How many communicators have mapped their influence networks? If you know who people go to when they want to know about something, then you can reach out to them and say, “What are people asking about?” And you can figure out what communication has been missed. But if you don’t know who those people are, you can’t do that. So we’ve been talking about mapping employee influence networks. I know Katie Macaulay likes seven different networks. If you can only do three: who do people go to when they need to know how to do something? Who do people go to when they need to know if something is true? And who do people go to if they want a reaction to what they’ve heard? So, “How do I do this? What’s going on? And should I trust this?” Those are three separate influence networks, and people tend to go to different people for those things. But if you can do some research and find out who those people are, then you can get ahead of this game. But I’ve got to tell you, I’ve been thinking about this. I’ve been thinking about using our intranet tool for a greater targeting of information to the audiences that care about it, and not sending it to the people who don’t, so that our communication is more relevant. And I have been thinking about our next internal comms survey. I’m going to rethink the questions around these issues, and then I’m going to think about a substantial change to our internal comms that may be phased in over a couple of years. But I absolutely see this applying to us. We have people out on project sites who are on ridiculous time schedules, and how much time they have to read a 2,000-word article is none. I don’t need to do the research to know that. So this needs a serious rethink.

Neville Hobson: What to do, indeed.

Shel Holtz: Yep. And that’ll wrap up this episode of For Immediate Release. We hope that you will comment on any or all of the stories that we have discussed today. Send email to [email protected], drop a recording in there and we’ll play it. It’s been forever since we’ve had an audio comment. We make it easy: if you go to the FIR Podcast Network website, you’ll see SpeakPipe voicemail on the right-hand side of the page, and all you have to do is record. You don’t need your own recording equipment for that. And then we’ll get it. You can leave comments on the post on this at firpodcastnetwork.com, or on LinkedIn, or on Facebook, or Threads, or Bluesky, where we share the release of each episode. We want to hear from you about these. And Vincent, we want to continue to hear from you. We enjoy your comments. We would love an audio comment from Vincent one of these days. And the next monthly episode will drop on Monday, July 27th. We’re planning to record that on Saturday, July 25th. But in between now and then, look for our short midweek episodes.

Neville Hobson: We have an interview coming up with Pete Blackshaw.

Shel Holtz: We do. Pete Blackshaw, who — I believe he was the first person we ever interviewed on FIR Interviews, wasn’t he?

Neville Hobson: No, he wasn’t the first, but he was in 2005 when we started. We’ve interviewed him three times, up to about 2009, and now we’ve got this long gap till now.

Shel Holtz: So looking forward to that. He’s talking about using artificial intelligence in order to figure out which product you want to buy, as opposed to other mechanisms, and why it’s better. I have lots of questions for him. We’re not going to get to them all. I’m sure you do too, but —

Neville Hobson: We do. Yeah, we’re interviewing Pete on Monday the 29th of June, and that interview should be published within a week or so of that.

Shel Holtz: Looking forward to that. And that will be a 30 for For Immediate Release.

The post FIR #520: AI’s PR Meltdown appeared first on FIR Podcast Network.

We have known about media bias effect for decades: the belief that the media is biased against your side of a debate. New research finds that the same belief applies to misinformation. While the research was focused on political issues, the underlying cause applies equally to misinformation about brands, companies, and business issues. In this short midweek episode, Neville and Shel find that the PR industry has not yet acknowledged the phenomenon, which requires strategies to address it.

Links from this episode:

• Think the Media’s Biased Against You? You Probably Think Misinformation Is, Too
• The Hostile Media Effect
• The Influence of Hostile Media Perceptions on Misinformation Beliefs and Sharing
• Hostile Media Effects on Twitter, Social Identity, and Media Bias Perceptions
• Fake News Has Real Effects on Consumer Demand
• The Impact of Fake News on Consumer Behavior and Market Outcomes
• Political Identity, Media Trust, and Susceptibility to Misinformation

The next monthly, long-form episode of FIR will drop on Monday, June 29.

We host a Communicators Zoom Chat most Thursdays at 1 p.m. ET. To obtain the credentials needed to participate, contact Shel or Neville directly, request them in our Facebook group, or email [email protected].

Special thanks to Jay Moonah for the opening and closing music.

You can find the stories from which Shel’s FIR content is selected at Shel’s Link Blog. You can catch up with both co-hosts on Neville’s blog and Shel’s blog.

Disclaimer: The opinions expressed in this podcast are Shel’s and Neville’s and do not reflect the views of their employers and/or clients.

Raw Transcript

Neville Hobson:
Hi everyone, and welcome to For Immediate Release. This is episode 519. I’m Neville Hobson.

Shel Holtz:
And I’m Shel Holtz. When you think about all the misinformation out there—fake news, bad-faith spin—do you think it’s mostly aimed at your side of an argument or the other side? Most of us, if we’re honest, feel like it’s aimed at us. And there’s now research saying that feeling is nearly universal.

Even though the research was based on political discourse, it has a direct connection to organizational communication. We’ll explain right after this.

All right, let’s start by backing up for a second. There’s a concept called the hostile media effect. It’s been around since the 1980s. The original study showed pro-Israeli and pro-Arab students the exact same news coverage of the exact same event. Both groups walked away convinced it was biased against their side.

Everyone saw exactly the same footage, but they reached opposite conclusions. And the more committed you were, the more certain you were that the media was out to get you.

That finding has held up for 40 years, and it’s a big reason trust in news has collapsed as politics has gotten more tribal.

Now let’s add the new wrinkle. A team at the University of Amsterdam asked whether that same instinct applies to misinformation—to fake news. They surveyed 4,000 people across Germany, the Netherlands, and Poland around the 2024 European elections.

Nearly half said their preferred party was particularly targeted by misinformation. Ask about the party they liked least, and that number got cut in half. They’re calling it the hostile misinformation effect, and it got stronger the more politically engaged people were. The more plugged in people felt, the more victimized they felt.

Now, Neville, you might think that’s a political science finding. But the mechanism underneath isn’t about politics; it’s about identity and motivated reasoning. Every brand, every company, every department is an identity group.

Your most loyal customers are partisans. Your most engaged employees are partisans. The research says the people most attached to your organization are exactly the ones primed to believe any criticism out there is unfairly targeting them.

Now think about a crisis. Your defenders don’t need convincing that your critics are unfair. They already assume it. The minds still open are the uncommitted people in the middle.

Among neutrals, knowing more made them see less bias. It’s only partisans who dig in.

So if someone criticizes a brand that some people love, the brand’s biggest fans may see that as an attack rather than just an honest review—and respond in kind. There was no crisis, but now maybe there is.

There’s an internal angle here, too. Picture a layoff memo or a return-to-office announcement. Leadership reads it as fair. But every faction inside the company—by department, by level, by tenure—is wired to read the same message as unfair to them.

“We said it neutrally” is no defense because neutrality is in the eye of the beholder.

This notion reveals a trap for communicators. When bad coverage hits, it’s tempting to wave it away as misinformation. But “fake news” self-destructed as a term the moment it got weaponized to mean “any story I don’t like.”

Cry misinformation every time you’re criticized, and you train your audience to tune out the label. You also look evasive to the exact neutrals you need to reach.

So this is where I want to bring you in, Neville. We’ve spent years on this show talking about declining trust and the misinformation environment. This research says the problem isn’t just that there’s more bad information out there; it’s that people are wired to feel personally besieged by it.

And I’m not sure our profession has reckoned with what that means.

Neville Hobson:
Yeah, it doesn’t sound like it, Shel. I don’t think so.

It’s actually quite fascinating looking at the Nieman Lab article you shared with me in our Slack channel and seeing the depth of the research on a topic that I had no idea was even a thing to look into.

I found it interesting in a number of areas.

For instance, the study you quoted from the 2024 European Parliament elections got me thinking. The tendency to see misinformation as directed at you seems more pronounced the farther right politically someone is.

That caught my attention because isn’t that precisely what we’re seeing in the United States with the Trump MAGA movement?

Here in the UK, we’ve got Reform and an even newer party that’s emerged further to the right. Those groups often function as an echo chamber for the kinds of messages Trump promotes. They’re constantly criticizing anything anyone else says as an attack and talking about issues in ways that rile people up and stimulate hostile reactions in return.

We see a lot of that in this country right now.

It’s interesting that this study has been done, and I think the way you’re connecting it to organizational communication is a good call. It certainly gives us a lot to think about.

One question it prompted in my mind concerns the point about engagement and partisanship. If the more engaged and partisan someone is, the stronger this effect becomes, does that mean an organization’s most loyal stakeholders are actually its most vulnerable to this kind of perception?

What do you think?

Shel Holtz:
Absolutely. I think that’s exactly the connection we can draw between this study and organizational communication.

If somebody criticizes the company based on an experience they had—and let’s say that criticism goes viral—and it was sincere and well-intentioned, then the partisan defenders of that organization are going to feel attacked. They’re likely to respond in kind and escalate a situation that probably would have faded into the background if left alone.

I think that’s one of the fallouts organizations can experience from this phenomenon. The more partisan you are, the more besieged you’re going to feel when you perceive something being said about the brand or organization as unfair—even if it was perfectly fair.

Neville Hobson:
So how do you address that within the organization?

Shel Holtz:
That’s an interesting question, and it’s hard to fight because you really can’t argue people out of it.

One related concept is the third-person effect—the idea that other people are more susceptible to media influence than we are ourselves.

In other words: I can see what the media is trying to do, but other people are going to be fooled by it.

When you stack that together with the idea that your group is being unfairly targeted, you get a complete worldview: I’m clear-eyed, my group is the victim, and everyone else is gullible.

There was a fascinating study where researchers took 661 Coca-Cola drinkers and showed them a real fake-news story—a 2016 hoax claiming that Dasani water was being recalled because parasites had been found in it.

The finding was that the people most confident in their own ability to spot fake news were the most convinced that other people would be fooled by it. They were also the ones most loudly demanding that Coca-Cola take corrective action.

Sometimes the stakeholders who are screaming “Do something about misinformation!” aren’t reacting to the actual threat. They’re reacting to a belief that other, less discerning people are being duped.

That makes the challenge even more complicated for communicators.

Neville Hobson:
Yeah, it’s weird, isn’t it?

The next question that comes to mind is this: If both sides feel targeted regardless of what’s actually out there, what should communicators do? Is there an approach that works when perception is this detached from reality?

Shel Holtz:
From an organizational standpoint—and I’m less interested in the political implications for purposes of this podcast—I think there are a couple of things.

First, the more prebunking you can do, the better.

When one of these situations comes up—a bad review, criticism from the media, negative reporting—you can immediately point people to information you’ve already published that addresses the issue. Having a bank of credible material you can reference may keep people from getting unnecessarily riled up.

The other thing is to respond quickly, but not emotionally.

If you can maintain a sense of calm—or even a sense of humor—you increase the likelihood that others will follow suit.

If people see that the company isn’t feeling besieged and isn’t acting attacked, that may help tamp down some of the reaction.

Neville Hobson:
So this becomes a major issue for trust, doesn’t it?

And I imagine the role of artificial intelligence in all of this only exacerbates the problem. Is that how you see it?

Shel Holtz:
Yeah, I do.

The flood of AI-generated slop out there—content targeting your organization, your brand, or your leaders—is only going to increase exponentially.

If somebody has an axe to grind and wants to flood search engines or AI summaries with negative content, AI makes that dramatically easier.

Now, to be fair, the research we’re discussing focused on information published through media outlets. That may be an important distinction.

People might be more skeptical of something posted on a blog or LinkedIn than something published by a mainstream news outlet.

That’s where this research suggests people feel especially attacked.

Neville Hobson:
That was my thought as well.

Going back to the study, we’re looking at this from a political perspective. We all consume information online, and most of us have preferred sources.

Meanwhile, mainstream media is going through what seems like a growing crisis of trust.

You see constant battles online between people citing one newspaper versus another. It’s distracting, and it wastes an enormous amount of time and energy.

It also got me thinking about how I react to some of this. The suggestion that people on the political right are more susceptible to this phenomenon doesn’t really describe me. I’m more in the middle.

I don’t react the way I see some people reacting—especially on that delightful conversation platform known as X.

People vent their spleens there. Maybe it makes them feel better, but I don’t think it advances understanding in any meaningful way.

Then again, perhaps that’s not the point.

The point seems to be: I win, you lose.

And that’s very much the Trump approach. It feels like that’s where much of this is headed.

Shel Holtz:
Yeah.

One of the stranger findings from the research was that when researchers examined whether people felt more victimized after their party lost an election, the results weren’t what you’d expect.

You’d think the losers would feel most targeted.

Instead, the people whose party won were more likely to believe their side was being targeted by misinformation.

Feeling besieged isn’t necessarily about being under threat. It’s about identity.

And since you mentioned X, there’s another interesting strand of research.

People may dismiss something because they saw it on X. But researchers found that the source of a message can trigger hostile media perceptions independently of the content itself.

Your company’s name on a statement can be enough to act as a bias cue for people who already have feelings about you.

The exact same words can land very differently depending on whose logo appears at the top.

That’s worth thinking about because it means message discipline alone can’t solve a credibility problem.

Neville Hobson:
This is a bigger dilemma than it might seem at first. A real conundrum for communicators.

The Nieman Lab article is lengthy, but it’s definitely worth reading.

Shel Holtz:
Yeah. And there will be links in the show notes to some of the original research on identity bias as well.

The reason I chose this topic is that I’ve never heard it discussed in PR circles. I’ve never seen it covered in PR textbooks or books about public relations.

This was completely new to me.

That’s one reason I’m still struggling with an answer about how to deal with it.

But it certainly starts with recognizing that it’s happening.

Neville Hobson:
I agree. It was new to me as well.

The more I think about it, though, the more it seems to describe the environment we’re operating in today.

Now we just have to figure out what to do about it.

Shel Holtz:
Yes, we do.

And that will be a 30 for this episode of For Immediate Release.

The post FIR #519: Is Misinformation Biased Against You? appeared first on FIR Podcast Network.

The history of public relations over the last 30 years is a litany of one failure after another — failures to recognize and embrace technologies that represented seismic shifts in how people and organizations communicate. The internet. The web. Social media. Smartphones. The video shift. And now, with AI, the industry seems poised to do it again. As many organizations explore how AI will reshape them, PR agencies still seem unable to figure out billing models to replace the now-useless hourly rate. In this short midweek episode, Neville looks at a post from Stephen Waddington that laments the industry’s intransigence, and Shel and Neville discuss what PR should be doing.

Links from this episode:

• The future of jobs in PR: will we get the third technology shift wrong too? (by Stephen Waddington)
• It looks like PR has its head in the sand about AI (by Neville Hobson)
• Senior practitioner neglect of digital/social skills a huge threat to PR’s future (2015 post by Shel Holtz)
• Once Again, This Time with AI, the Communications Profession Will Be Late to Embrace a Valuable Technology (2023 post by Shel Holtz)

The next monthly, long-form episode of FIR will drop on Monday, June 22.

We host a Communicators Zoom Chat most Thursdays at 1 p.m. ET. To obtain the credentials needed to participate, contact Shel or Neville directly, request them in our Facebook group, or email [email protected].

Special thanks to Jay Moonah for the opening and closing music.

You can find the stories from which Shel’s FIR content is selected at Shel’s Link Blog. You can catch up with both co-hosts on Neville’s blog and Shel’s blog.

Disclaimer: The opinions expressed in this podcast are Shel’s and Neville’s and do not reflect the views of their employers and/or clients.

Raw Transcript

Shel Holtz: Hi everybody and welcome to episode number five hundred and eighteen of For Immediate Release. I’m Shel Holtz.

Neville Hobson: And I’m Neville Hobson. So here’s a question I want to put to you right at the start, and I’d like you to sit with it as Shel and I work through this topic today. Public relations as a profession has faced two seismic technology shifts in the last 30 years. In fact, more than two, but I’m just going to mention these two. The internet arrived in 1995. Social media arrived around 2007. And in both cases, PR largely got it wrong. Not wrong in the sense of ignoring the technology. Wrong in the sense of fundamentally misreading what it meant. In 1995, we thought the internet was a publishing problem. In 2007, we thought social media was just another broadcast channel. And the disciplines that grew out of both—search, content marketing, influencer marketing—were largely built by people who weren’t us, people outside the profession who saw what we missed. So the question is: are we about to do it a third time? We’ll address that question in just a minute.

That’s the challenge Stephen Waddington lays down in a piece he’s just written for Influence, the member magazine of the CIPR, the Chartered Institute of Public Relations. Stephen is someone whose thinking I respect considerably. He’s been one of the sharper and more honest voices in UK PR for years. And this article comes off the back of a book he’s just co-edited, AI and Public Relations: A How-To Guide for Implementation and Management, published in May. And what he’s arguing in this piece is that this is no longer a theoretical debate, as job reductions are happening now. He gives specific examples. Three account executives doing media monitoring—that’s now one tool. A two-person intranet team—that’s now a fraction of the effort. The UK government has listed public relations professionals among the twenty occupations most exposed to large language models. We’re on the list. Early career employment in those sectors is also in relative decline.

Now, Waddington is not a pure pessimist. He sees a plausible optimistic path. The career pyramid becomes a diamond. Firms building roles around insight and risk management rather than billable hours. A rough near-term reduction of perhaps fifteen to twenty percent in entry-level positions, followed by net growth as scope expands and new roles emerge, the way digital did after 2000. He thinks in-house teams especially have an opportunity here. When AI absorbs the routine, it frees space for the work that corporate communication teams have always needed but rarely had capacity for. But he gives serious, genuine weight to the pessimistic case too. And this is where I think the article gets interesting. He references Martin Ford, author of The Rise of the Robots in 2015, and Ford’s argument that previous technology waves hit one tier of the workforce and the tier above absorbed the displaced.

This time Ford says there’s no tier above. The advisory work that absorbed previous shifts is itself the target. Waddington doesn’t fully accept that in his article, but he doesn’t dismiss it either. And then there’s the argument that I think should be keeping every agency head and comms director awake at night—the pipeline. He’s hearing a common response from firms right now: freeze your apprenticeship schemes, freeze your graduate intake, let AI cover the production work. And he calls that, bluntly, organizational self-harm. Because in five years, those organizations will have nobody who understands how the systems actually work, why they fail, and crucially when to override them. You cannot run an advisory profession without a pipeline. And you cannot build a pipeline if you spent five years dismantling the entry points. So that’s where I think we should start today’s conversation. Not with the technology, with the choices.

Because Waddington’s closing argument, and it’s what I find compelling, is that human agency still exists here. The technology isn’t making decisions. We are. The question is whether we’re making them wisely, or whether for the third time in thirty years, we’re about to hand the future of our profession to people who aren’t us. Shel, what’s your instinct on this?

Shel Holtz: Very much what yours and Stephen’s is. I have been saying for decades that the public relations industry is always, always, always late to the game when there is a new technology that is going to shape the way communicators do their jobs. We were late to the internet, for sure. We were late to the World Wide Web. My first book on communicating online—well, actually, my first book was on intranets, but the first one that got any attention was Public Relations on the Net—came out before the World Wide Web, before there was a graphical user interface. So there were plenty of opportunities for PR before the web, based on the capabilities of the internet. Then we missed the web, then we missed social media. In between we missed some other seismic shifts—mobile, being able to communicate with people based on the fact that they now had this computer in their pocket. We missed the pivot to visual communication, we missed the pivot to video communication. And now, yeah, we are poised to miss the pivot to AI. And that’s not to suggest that PR people aren’t using it. I think they are, but I think they’re using it at a very superficial level and are succumbing to a lot of the hype out there about things like job loss and “get rid of your entry-level people.” That’s all mundane drudge work that the partners and senior people don’t want to do—the account execs—so hand that all off to the AI and you don’t need to pay those people anymore.

And you’re exactly right. I was listening to a podcast over the weekend where they were talking about the same issue, but they were talking about it in the context of law firms. And they were making the point that the associates that are brought in out of law school do the drudge work that the partners don’t want to do. They write contracts, right? They do things like that. And now that the AI can do that, who needs them? Well, the question becomes: where do the future partners come from when the ones who are already at the partner level retire? There’ll be nobody to take those jobs. We are not rethinking the industry, and we’re not rethinking it from two perspectives. One of those perspectives is the agency. The other perspective is the in-house side of communications. They’re two sides of the same coin. But I think we need to split them apart and look at them in terms of how we need to reinvent the profession. You and I have talked about reinventing how we bill, how we price, because the hourly model makes no sense anymore. But what does an entry-level person do if the AI can handle a lot of that drudge work? And it can.

I mean, we’ve talked about on this show that I’ve set up a Hermes instance and it is out there. In fact, I haven’t checked my Telegram account yet, but there should be 10 links to recent news stories that are prime for me to news-check because I set up an agent to do that. I have an agent set up, a skill set up, that I can deploy anytime I want to. It is set up to analyze the websites of twenty-two of our competitors. And all I have to do is tell it what I want it to analyze. Do I want it to look at how they handle their project portfolios? Do I want it to look at how they handle their thought leadership? I can ask it any of those questions and it’ll come back and give me a very nice report. I could absolutely set it up to do media monitoring. I’m starting to question the need for my media monitoring service at work, although the agent that I have set up to do some of this certainly can’t get behind the paywall the way that the media monitoring service can, because they pay the licensing fee for all of those. So if the AI can assume all of this work, it’s not a question of saying we don’t need entry-level people. It’s a question of reimagining what entry-level people should be doing.

In terms of AI: What should they be doing with AI, and what new things can we be having them do that we haven’t thought of before, or that we always wished they could do if they didn’t have all of this drudge work that they had to spend their time on? It’s time for a reinvention, and I don’t see anybody talking about that. I haven’t seen a whole lot of ideas about where all this should go.

Neville Hobson: Yeah, I’m with you on that a hundred percent. Exactly my sentiment as well, that you don’t see people talking about this in a truly serious way. I see on LinkedIn—if that’s any barometer, I don’t know if it is or not—but I see people mentioning this now and again and “we ought to do something about that.” But there’s no webinars, no seminars, no get-togethers on the topic of reinventing the agency, let’s say. It’s a topic I’ve written about myself, and value-based pricing versus time-based pricing. And it’s interesting how Stephen Waddington addresses that topic in his article. It’s quite a pointed observation he makes that’s worth pushing on. If you’re still selling time rather than value, he says, AI will break your model. That’s a direct challenge to the billable-hour structure that much of agency PR still runs on. So the firms getting this right are building around insight, outcome, and risk management instead. It’s worth asking how many firms are actually making that structural shift versus just talking about it. Not enough. Doesn’t mean to say they’re ignoring it. Far from it. I think it’s largely because they don’t know what to do. How do they address this? So there’s an opportunity for someone with some insights and answers to help educate firms like that. There’s a consulting opportunity, if you like.

Shel Holtz: I was thinking exactly the same thing. If somebody’s looking for a pivot in their career, that sounds like one to me.

Neville Hobson: Yeah, yeah. So we are at that place. Again, go back just three years, 2023, when we wrote our pieces about that CIPR survey, and twenty-five percent of the respondents said they’d never ever use AI. It was pretty absolute, the answers. Here we are, three years later, and I bet you that number’s down to five percent, if not less. I can’t imagine anyone—and it causes a very broad question, “would you use AI, yes or no?” It’s a bit like “should we stay in the EU, yes or no?” I mean the Brexit referendum—well, people, what a dumb question. But so that’s where we’re at. But I believe a lot of the landscape is now so polluted with everyone’s opinion that it’s very confusing to zero in on what are the issues I need to be thinking about in an organization. Plus, I see so many people—I saw one just this morning—someone’s got a PDF book on how to move your business to selling value, basically, not time. And it’s not how many hours you did, it’s what did you deliver to the client.

So it’s great, but it needs to be more authority than that, I think. And this is where the profession comes in—professional bodies like the CIPR, the PRSA in the US. The CIPR has done a good job in raising awareness about AI in the right way, in context related to public relations. They’ve had this AI panel for some time now with senior practitioners leading it. This book’s come out and it’s got a lot of support from practitioners in the UK and beyond. So maybe now is the time that this is going to get taken a bit more seriously than people do. I think though what Stephen worries about—and I think it’s not a misplaced worry—is the point that people are being laid off. Layoffs are happening all the time and most people believe it’s because AI is going to be more efficient and all that kind of stuff. And there must be some truth in some of that. But he also mentions something quite interesting in his article, because he says that most of the conversation about AI and jobs focuses on redundancy risks from above—leadership cutting roles. We’ve talked about that quite a bit. But Waddington notes a quieter pressure running in the opposite direction. Junior and mid-career practitioners are walking out of organizations they consider too far behind the curve.

So firms that move too slowly aren’t just at risk of getting the technology wrong, they’re at risk of losing the people who could help them get it right. The talent drain is bi-directional. Now that’s an interesting element to bring into this discussion, I think—that it’s those folks who are walking away. He doesn’t say, and I hadn’t found anything before we started recording, as to where they’re all going. Are they leaving the profession entirely, or are they just looking for a place that—in a sense they feel it’s worth going to this company because they’ve got it switched on, that they’re clued into this? So maybe that’s the state we’re in. Doesn’t answer the questions, mind you, and they’re coming thick and fast now, I think. I see, again, LinkedIn is a kind of barometer of sentiment, if you will—not in the analytics way, but the feeling you see expressed in some posts from some people who are worth reading about it. And that includes many of the people that I follow and that you would follow as well. So you’re seeing this, but it’s all very random. That’s the thing. And it requires something more than that. And voices like Stephen’s, yours when you were talking about this—we’ve missed about three, four, five times, that sort of thing. What’s going to make people really pay attention to this?

Shel Holtz: I hate to say it, but it’s the same thing that has always made the industry pay attention, and that’s when they suffer financial pain. The reason we have not embraced as an industry these technological changes is our billings were fine. We were doing just fine as an industry financially. So why should we make this risky change to something that we don’t quite understand and we’re not convinced is going to have all that much impact or will necessarily stick around all that long? That leaves an opening for other industries—advertising and marketing—to sneak in. It also leaves an opportunity for boutiques that specialize in this to start up and take money off the table that was there for the PR agencies that were already in business. And this seems to be a recurring pattern: if we’re not feeling the financial pain, we’re not gonna make any change. As soon as we start to feel that pain, as soon as we see our clients going to the boutiques and going to the marketing agencies, then we go, “we better change.” And then we’re behind the curve. So I think that’s the big issue and the big challenge—to be proactive rather than reactive when these technologies create these opportunities, or create the requirement, if we wait, that we must change because we’ve already seen these revenues go to somebody else.

One thing to keep in mind: absolutely there have been layoffs within the industry and they have been attributed to AI. It is important to keep in mind though—and this was reinforced in that very same podcast I was listening to that I mentioned earlier—that if you look at economic data, there’s no evidence of mass layoffs as a result of AI. The unemployment rate is pretty much where it was before all of this. The number of new jobs that are being reported, at least in the US, has actually been pretty strong. The jobs report the last month was quite encouraging. So we keep hearing about the mass layoffs and they may be coming. They may not.

Because frankly, what I see—and I don’t know if this is unique to the construction industry, I doubt it; I think it may be a bigger issue in the construction industry, but I think this is probably true of most jobs—is it’s not the job that gets replaced by AI, it’s tasks within the job. And then there are other tasks that the AI can’t do. The other thing is that there are things that we have wished that we could do, but haven’t had the time to do, from an internal comms standpoint and even, I suspect, a PR standpoint from inside the organization, the client side. I mean, I remember when I was in my first corporate job. This was with Arco. I was there from ’77 to ’83 with some brilliant communicators, but the company believed in it. So they funded the internal comms department. We had 25 employees in internal comms in five cities.

And each of us had beats, just like you were a newspaper reporter with a beat. I had two beats. I had Arco Petroleum Products, which was the gas stations and the merchandising of cans of motor oil and things like that, and Arco Marine, which was the oil tankers that transported oil mainly from Alaska down to the refineries along the West Coast. And I spent time—I mean, that was my job, was to go hang out, to spend time, to shadow somebody, to do a ride-along, to ride on a tanker, to spend a day at one of the gas stations and really get a sense, and to be able to report on this a little more intimately than just calling somebody and doing an interview over the phone. And in public relations, I think it’s important to remember that “relations” part of the public relations label. How do you build relations? Well, if AI really does take away a lot of that drudge work that we spend the time doing while we’re sitting at our desk, then we have time to get up from our desks and go out and hang out with the publics that we are dealing with and build those relations. And why wouldn’t we want to do that? AI can’t do that. AI can’t get up, get their car and go to where the public is. Maybe it’s a community relations organization, maybe it’s a division of your business. Maybe it’s a customer base that is gathering—well, let’s say it’s Ford Motor Company and there’s a car club that’s meeting. Whatever it may be, we have the opportunity now to become much more entwined with those publics.

And do a much better job of understanding them. Yeah, we still want to do the data, we still want to do the analytics, but there’s nothing like sitting with them and looking them in the eye and talking with them to build an understanding that’s going to help you communicate with them and help you build trust among them. That’s just one idea of what we can do with this freed-up time. And this is an important point—and I saw this in one of the reports that came out just last week, I think it was—the value that we get from saving an hour because AI can do it just leaks out of the bottom of the organization if we don’t know what we’re going to replace that hour with that has value. And we hear about all the savings of time that AI is going to give us. I haven’t heard a whole lot about how organizations are figuring out how to reallocate that time among those employees.

Neville Hobson: Yeah, yeah, neither me. No, I agree. And you do hear a lot of talk about the concept of that. I mean there’s lots in this topic, Shel, really, and you’ve thrown some bright light on some of the things we should be doing. I like the idea of going out to meet your publics, as it were. It’s winding the clock back, actually, to how we used to do all this back in the day, before all this tech was there.

Shel Holtz: Yeah, it really is.

Neville Hobson: We had to go out and find the sources and interview them face to face and, you know, meet down the pub or whatever. So maybe we need to examine what worked in the past and bring it to the fore again.

Shel Holtz: When I was a newspaper reporter, before I made the switch to corporate communications, I was with a local community daily newspaper, and I used to go hang out at the bar after work where all of the government workers hung out after work. Got to know them, got to listen in, got some pretty good stories out of that. But also I could pick up the phone and call some of these people because they knew me. I wasn’t just the reporter who called when I needed a quote or needed some information. I was the guy they just had a drink with.

Neville Hobson: Yeah, exactly. Lessons to learn there, I think. So yeah, lots of good ideas here. I think Stephen Waddington did a good job in literally describing the landscape and expressing some of his concerns. That’s prompted this conversation. So let’s hope this adds to the topics that people need to be talking about. So listeners, hope this is helpful.

Shel Holtz: And listeners, if your organization is actually making some changes and doing some pivots, we’d love to hear about it. And that’ll be a 30 for this episode of For Immediate Release.

 

The post FIR #518: Is the PR Industry Blowing It Again? appeared first on FIR Podcast Network.

First, they were told to use AI. Experiment! Add it to your workflows! Go wild! Then the bills started piling up, and companies realized the cost was not tenable. Now the walk-backs are happening. Usage caps! Caution! Slow down! Among the issues communicators need to address is employees questioning leadership’s judgment. In this short midweek episode, Shel and Neville explore approaches communicators can take to help employees understand the pivot while maintaining the perception of leader competence.

Links from this episode:

• AI can cost more than human workers now
• Microsoft reports are exposing AI’s real cost problem: Using the tech is more expensive than paying human employees
• When AI Costs More Than the Worker It Replaced
• AI isn’t paying off in the way companies think. Layoffs driven by automation are failing to generate returns, study finds
• AI layoffs may be backfiring on companies
• Uber, Microsoft, and Others Burning Through AI Budgets. Now What?
• Uber burned through its entire 2026 AI budget in four months. Now its COO is questioning whether it’s worth it
• Uber Burns Its 2026 AI Budget In Four Months On Claude Code
• Sam Altman says OpenAI’s top token spender uses 100 billion tokens a month — and they’re not even the world leader
• OpenAI CEO Sam Altman admits AI token costs are becoming ‘a huge issue’ — company seeks improved value as overspending becomes a meme
• Token Billing Exposes AI’s Missing ROI And Puts Billion-Dollar Bets At Risk
• AI savings misses should make executives uncomfortable
• AI saves workers a day a week, but they don’t know what to do with it

The next monthly, long-form episode of FIR will drop on Monday, June 22.

We host a Communicators Zoom Chat most Thursdays at 1 p.m. ET. To obtain the credentials needed to participate, contact Shel or Neville directly, request them in our Facebook group, or email [email protected].

Special thanks to Jay Moonah for the opening and closing music.

You can find the stories from which Shel’s FIR content is selected at Shel’s Link Blog. You can catch up with both co-hosts on Neville’s blog and Shel’s blog.

Disclaimer: The opinions expressed in this podcast are Shel’s and Neville’s and do not reflect the views of their employers and/or clients.

Raw Transcript

Neville Hobson: Hi everyone and welcome to For Immediate Release. This is episode 517. I’m Neville Hobson.

Shel Holtz: I’m Shel Holtz. In some companies right now, that AI that was supposed to replace expensive humans is costing more than the humans it replaced. The numbers are kind of breathtaking. Uber burned through its entire 2026 AI budget in four months. In fact, I just heard today that they’re introducing a monthly AI spending cap of $1,500 per employee. One unnamed company, a real one though, spent half a billion dollars on AI in a single month because nobody had bothered to set a spending limit. An NVIDIA executive flat out admitted that for his team, compute now costs more than the engineers using it. A lot of these companies didn’t just overspend, they made decisions on the strength of what they thought AI could do. And in plenty of cases, those decisions cost people their jobs. The pitch was that AI can do this work for a fraction of the cost.

Then Bain and Company studied a thousand companies and finds that most aren’t getting those savings. Gartner found the layoffs delivered no better returns than not laying anyone off at all. In its study, Bain looked at the books and saw money leaking out of the top, companies spending the budget without the savings showing up. And Boston Consulting Group went and asked employees and found that the leak runs from the bottom too. Over 40% of regular AI users say they’re saving a full workday every week. But Boston Consulting Group’s point is that saved time doesn’t automatically become value. If nobody tells an employee where to redirect those reclaimed hours, that value just evaporates. So two consultancies looking at two completely different ends of the organization landed on the same diagnosis. This is a management failure. It’s not a technology failure. So put yourself in the shoes of employees who are still there.

They watched colleagues walked out the door because they were told the machine could do it cheaper. And now they’re watching leadership start to walk it back. In most cases, walk it back really quietly. What does that do to employees who see their leaders’ judgment, their competence? Because that is where this becomes a communication story. It’s about trust, credibility, and what we as communicators are supposed to do when leaders make a big public painful bet that doesn’t pay off. We’ll share our thoughts about that right after this.

Now there’s a lot we can talk about with this story, like communicating a suddenly altered governance model. But let’s start here. The bet companies made was about people, that AI could replace human labor at a fraction of the cost. When that turns out to be wrong, employees don’t just see a line item on a P&L. They see leaders who either didn’t understand the technology they bet the company on, or who used the AI story as cover for cuts they were going to make anyway, what we’ve come to call AI washing. Both of these readings are poison. The second one travels fastest. A communicator’s first job is to make sure that the accurate story is the one that gets out there. And to add a little context to that idea, Sam Altman, the CEO of OpenAI, just recently said that this cost discussion is new. It started early this year. Before that, nobody was talking about it. And that’s probably because before early this year, most employees were prompting AI chatbots, and that didn’t blow up budgets. What changed early this year? Agents. Now employees have agents running complex tasks in an endless loop, and that burns tokens like nobody’s business. I heard about one employee who burned through a billion tokens in a month. That means costs are exploding. It’s not something anybody really anticipated, and a lot of CEOs were caught unaware. You know, they paid for the subscription cost to say Anthropic, now they’re paying the subscription, but they’re also paying for tokens. So Neville, if you were leading a comms department in a company that laid off a bunch of people because AI could do their jobs, and now it’s either costing more for the AI to do those jobs, or the AI isn’t doing it as well as the people did, how do you communicate that without making leadership look like fools?

Neville Hobson: Yeah, it’s a good question, isn’t it, Shel? I mean, you’ve painted a picture that’s pretty dire, it seems to me. And I like to think that this is a kind of outlier territory we’re in. This is not the mainstream. But I’m willing to be proven wrong. You know, I don’t recognize this in the UK, so it could not yet be a big deal over here. But I’m thinking you mentioned that the original AI narrative, if I can describe it that way, was sold to people as we’re replacing you with robots or we’re replacing you with tech. I wonder, is that the case everywhere? Because I would have thought it was, many would have sold it as additive. It’s AI plus you, not AI instead of you. And that’s a wholly different kind of message if that were the case. Either way, they’re walking it back. And I think there’s a handful of things the communication leader should do. And that person would also be the counselor and the advisor to the leadership of the organization. So I think one of the first things, if not the first thing, is that you mustn’t let the leadership hide behind euphemisms. You know, restructuring, right sizing, optimizing for the future, that kind of stuff.

Employees see through all of that, particularly in this example. And it makes things even worse, I think. The communicator’s job is to push for plain language, even when that’s uncomfortable. So that’s one thing. The second, and again, this may well be the first. I’m just putting these out there as bullet points effectively without saying which is the most significant. Acknowledge the whiplash directly. Acknowledge it. Don’t pretend that the earlier message just didn’t happen. All those lovely messages about this rosy future’s coming when we’re introducing AI. You could say, we told you AI would be a productivity multiplier for everyone. We believe that. The reality has turned out differently, and you deserve an honest explanation of why. Of course, your next bit is so what are you going to say? But that’s the framing you need to do. Separate the human cost from the technology story. The people losing jobs are not a line item.

Communication that treats them as a budget adjustment will destroy trust with everyone who remains behind. And the people who remain are watching very carefully. Give the survivors something real, not platitudes about the future, concrete information about what the new operating model looks like, what’s expected of them, and what support they’re getting. And there’s a harder truth for communicators, it seems to me, and this kind of popped out of the woodwork sideways when I was looking into this. If you’re the comms person in a situation like this, and leadership won’t let you be honest, won’t acknowledge the contradiction, they won’t speak plainly to people losing their jobs, then you have a professional and ethical problem, not a communication problem. And that’s a different ball game. And if you’re in that situation, I would say, easy to say this naturally, is get your resume brushed up and start looking around someplace else. You don’t want to be in that kind of environment. So the best communication advice in the world can’t fix a leadership team that wants to paper over a broken promise. And that’s worth saying out loud. And I think these are the things that should be on the communicator’s to-do list in a situation like this that could, I suppose, go some way towards restoring or maintaining some level of trust in the leadership, where we do, we hate what you did, we’re angry at you, but we believe that you are willing to fix it in some form. And even saying like, yeah, I’m with you on that, you thought this would work and it didn’t. So there’s other questions that will arise too. But either way it’s going to be an uncomfortable journey to get to an outcome that you like.

Shel Holtz: Yeah, to your first point, no, I don’t think every organization is going through this. I think it’s the ones that are actually providing employees with a budget to use tokens. I mean, we heard the stories about the leaderboards that were encouraging people to rise to the top of the leaderboard for the number of tokens they were burning, because that would indicate, it would signal that they’re using AI, which the companies wanted them to do. But you know, the models, the frontier labs were not really forthright with their pricing structures on the tokens. This was something new. They introduced it. It’s not very transparent. Not all of them even have the ability to show you how many tokens you’ve burned through. A couple of them do, but it’s not clear what that means in terms of your costs or what you have left available. But you know, from the communication standpoint, yeah, the trap I see here is that the original decisions were announced really loudly.

Shel Holtz: They issued press releases. They had all hands meetings. It was discussed on earnings calls. The correction here is happening more like a whisper. Spend caps are being added quietly to governance language. I know Uber is out there talking about it, but not everybody. The leaderboards for those token maxing exercises are just vanishing without explanation. Contractors are appearing in company offices to do the work that the AI was supposed to do. Some of them are the employees who were laid off in the first place. So, you know, when you boast loudly and walk back quietly, employees are going to fill that silence, right? Information abhors a vacuum. And they’re going to fill it with the worst possible interpretation. But, you know, leaders do have this instinct to either double down, you know, this is what we said we were going to do, and by God, we’re going to do it. Or they go quiet, and both those approaches are wrong. I think what actually rebuilds credibility isn’t a groveling apology. It’s a clear here’s what we expected, here’s what the data actually showed, and here’s what we’re changing in response. I think that reframes what looked like a wrong bet into a process that we employed to arrive at the best outcome.

And it’s a continuum, and we’re here at the continuum. We’re not at the end game. We’re still learning and adapting and adjusting, and we still believe in the promise of AI, which by the way, I do. Look, employees don’t lose respect for leaders who update their thinking. They lose respect for leaders who pretend they were right all along when they weren’t. So we should counsel leaders to stop measuring AI adoption and hours saved, and start measuring whether that saved time is actually being reinvested into something that matters. We should never have been celebrating who can burn through the most tokens the fastest. In communication terms, that’s like focusing on which communicator can produce the most articles for the intranet and ignoring whether people are modifying their behaviors or reinforcing their support for company goals or whatever other outcomes you had determined that those articles were supposed to produce. Deciding what an organization celebrates, what it puts on the scoreboard, that’s partly our job.

Neville Hobson: Yeah, I’d say you’re right. It’s interesting. I think there’s a kind of an underlying question behind all this, it seems to me, that I was mulling over when I was looking at this. The real question is, can communications actually repair the damage that’s been caused by this? Can it? I think the honest answer is partially. So good communication can reduce the damage, preserve some trust with the people who stay and give the organization a chance to rebuild its credibility over time. But it can’t undo the promise. It can only help people understand what happened and why. Now that may sound like, well, in that case, this is doomed. No, not at all. Because if you get to that point, help people understand what happened and why, you’ve then got a foundation where you can build from, it seems to me. And that’s connected directly to your point you just made, that you have to, you know, grasp the nettle as it were, take the bull by the horns, etc., think of the metaphors, and be honest and truthful, fess up. It’s not like, yeah, we screwed up, not at all. We made the bet, we had all the research, everyone was convinced this would work, and indeed our vendors who persuaded us to sign up for all those tokens were saying the same thing.

There’s also another element. I’ve been reading about this in, I’ve forgotten, one of the US papers that I subscribe to, about this supposed huge AI backlash in the US that isn’t happening here. Yeah, it’s not happening here, although it’s a whole different landscape here in that context. Not on the scale that you have in the States. But I’ve been reading a bit about that. Maybe that needs to be factored into this as well, because that would fuel people’s anger, I think, at the outcome that they’re experiencing, particularly if there’s kind of iffy communication somewhere in there that doesn’t resonate with employees. So it’s a complex picture. But I think the real question is, can communications actually repair the damage? And I think the answer is precisely that, partially.

Shel Holtz: Yeah, you raise a really interesting point. If 70% of the population is feeling negative about AI, you have to figure that that is reflected in your employee population. And now you’ve got this piled on top of that. That’s just fueling those views. So you have to factor that into the approach that you’re taking to communication and maybe even into the employee profiles that you’re using to craft those communications on that whiplash that you were talking about. Important to remember that for, you know, like a year, employees were pushed. Yeah, there were mandates, those leaderboards I mentioned. They were pushed to use it as much as humanly possible, and now they’re being told, oops, use it carefully. Yeah, and I think communications does set the narrative that connects those two poles. You know, without it, the reversal just looks like leadership didn’t know what they’re doing.

Shel Holtz: And again, that reads as incompetent. So I think we do have to build the bridge. We learned something on the road. Here’s what’s changed and why. It doesn’t mean that the promise of AI isn’t still there. It’s just the road that we are taking to get there is a little more winding than we expected. And by the way, speaking of the whiplash, according to that Boston Consulting Group survey, nearly half of workers, 47%, say they spend more time managing and directing AI than doing the actual work they were originally hired to do. Think about that against what leaders promised, because the pitch was that this was going to be a labor-reducing thing, a productivity improver. And what employees are actually living is the labor didn’t get easier, it just got transformed from doing the work to supervising the AI that does the work. Boston Consulting Group found that four in ten reported an increased cognitive load, which is, I have to say, exactly what I have been experiencing. I’m not spending less time, I’m spending more time, and AI is part of the reason for that. So when the lived experience doesn’t match what was said in the announcement, the gap is where leaders’ credibility can go to die, right? It’s the communicator’s job to close that gap. Make sure that the story leadership is telling matches the work that people are actually doing and the experience they’re actually having.

Neville Hobson: Yeah, I would subscribe to that view. I’m also thinking, Shel, that, you know, the way this has been presented, let’s say, is as if, you know, lots of communication when this started, big promises from leadership, and then silence. And now there’s this, we’ve got to rethink all this and you’re not going to be able to do that. So there was no effective communication in the meantime, there was no updates on what’s going on and this is what people are doing and these are the benefits they’re having. So I feel there was a lack of continuity in the communication. Otherwise this wouldn’t have landed as a big surprise, or as big a surprise as it has to many. There would have been signs that might have prompted some to say, whoa, hang on a second. I’m getting this little note here saying I’ve used so many tokens. I mean it could even be, what are these tokens it keeps talking about? How was that communicated? That every time you do this, this is going to happen. And I’m thinking of my own experience as an individual and the experiments I’m running with Claude, for instance, that when I was experimenting with Claude Cowork, it would, or it might have been the project, I can’t remember which one it was now, but there was a little script I could put into the model that told me how many tokens I used. And it didn’t tell me that and then some kind of tech gobbledygook that I wouldn’t have a clue what the hell does that mean. It actually told me this project you’ve done used so many tokens, which is nought point one two percent of your total allowance until the next reset. Now that makes me think, that’s okay.

So, did they have anything like that in the organization that enabled people to just keep a running total on what they’re doing? You know, it’s kind of like the average MPG in your car kind of thing. Everyone knows that kind of thing. That’s helpful, even though it’s not very scientific or detailed, but it would be enough. And maybe I haven’t encountered it myself. I see people talking about this on LinkedIn quite a bit, where they are getting fed up with this tool telling me I’ve reached my token limit, and I’m thinking, okay, they’re obviously doing the kind of work that not everyone is doing that burns through tokens like this. And it’s quite tech oriented, those kind of comments. So you’ve got to take that into account. But I think it does come back to, from a comms point of view, that you told people this is what was going to happen, this is why we were doing this, and there’s this lovely rosy future for all of us. Did you explain the detail about how things were going to actually happen? Probably not, I would say. So otherwise there wouldn’t have been the backlash at the end. The backlash would have started earlier and you might have been able to head it off. You might have been able to make a difference. So these are all, you know, what-ifs perhaps, but nevertheless, it comes back to that underlying question, that can communicators actually repair this? The answer is partially, it seems to me.

Shel Holtz: Yeah, and I could definitely see myself burning through a lot of tokens without a tech rationale for it. If I set up ten agents to scan the media environment 24 hours a day, seven days a week, each with a different area of focus, and they’re just constantly running, that’s tokens being burned. That’s like the car never being turned off and going through the gas. So, by the way, imagine the message that companies can send to their employees if the company was more deliberate and slower about the implementation of AI. They know it’s coming. They’ve given Copilot to employees, but in terms of everybody going out and building agents and things like that, well, we’re still remediating our internal data to make it useful for an AI model. And we haven’t launched our training yet. No, they can rub their hands and say, you know, being slow and deliberate paid off. Look what’s happening to all these other organizations. We’re pretty smart leaders here in this company. By the way, one other communication opportunity I want to address before we wrap up, and that’s around governance, because there’s, you know, a remarkable detail in this story. The companies that overspent mostly already had the tools to prevent it. You know, spend limits like you set up in the agent that you had that told you how many tokens you’d gone through. Routing simpler tasks to cheaper models. I just heard this morning on a podcast that there’s something you can sign up for if you use their tools, it’s automatically going to route you to the right model for the task. So you’re not always using the high-end model, the reasoning model, the thinking model, that costs a lot. Budget caps, all of these rules have always existed as capabilities inside the platforms, the companies just never switched them on. So for a communicator, that’s a gift because it lets leadership say we’re putting real discipline in place without it sounding like punishing employees for using too many tokens, like they were initially told to do. The framing here is everything. The governance change needs to be framed as here’s how we make sure this actually pays off for us. And it lets employees know the company’s approach to AI is maturing. If you frame it as AI use is now restricted, well, that signals panic and confirms the exact incompetence story you’re trying to tamp down in the first place.

Neville Hobson: Yeah. Again, what was communicated, how was it communicated, to what depth was it communicated, and how did you know that people absorbed it well? So what kind of feedback mechanism did you have to see if people understood the message? But I think there’s also another element, this is an organizational one, which is, you know, you’ve got a hundred and fifty employees, let’s say you’ve got five hundred employees in your company, did every single one of those five hundred need unlimited token access to do anything they wanted? No, they shouldn’t have done. So the example you mentioned, a tech person or enabling someone to be monitoring something twenty-four seven, not everyone would need to have that. And in fact, you’d need to structure it so that only these guys who need to do that. And I would imagine you’ve done a comparison to say this is definitely going to be cheaper than doing it that way, which you’ve always been doing it. So that would make sense. I wonder how many didn’t even do those kind of, you know.

Shel Holtz: Many, if not most. Yeah.

Neville Hobson: Right, I wouldn’t be surprised. So perhaps we shouldn’t be surprised at this outcome that we’re discussing here. And again, that is now the fifth time I think I’ve mentioned this, that communications can only repair this damage partially. And I think the bits it can repair are going to have some good outcomes, I would say.

Shel Holtz: One other thing that communications can do here is to set the stage. It’s, this is not the end game. We have not reached the place where, now we get it, everything’s right. The message is anticipate more change from this. I mean, the frontier model companies, Anthropic, OpenAI, you know, they’re going to change their pricing models because they know that people are dissatisfied. They know that it’s opaque. They know that it’s costing more than people and companies can afford. So you can look for this to get changed. I just recently heard somebody suggesting an outcome-based pricing model as opposed to a token-based model. I don’t know how that would work, but it’ll be interesting to see what they come up with. But you need to prepare employees for more change. You can’t let them be surprised again. Look at what agents did to the way this has pivoted. There’s going to be more of this on the horizon. You know, prepare yourself, but in the meantime, we are still on the right path of figuring out how to apply this to the organization’s best advantage. And that’ll be a thirty for this episode of For Immediate Release.

The post FIR #517: How to Communicate AI Whiplash to Employees appeared first on FIR Podcast Network.