We live in a world where recruiters can connect with thousands of people with a single click. LinkedIn, CRMs, and AI tools all promise to manage relationships at a scale unimaginable a generation ago. 

The challenge is that genuine trust doesn't scale automatically. When interactions become automated and transactional, the very thing that makes recruiting work starts to break down. People still hire people they trust, and the best referrals still come through relationships, not algorithms.

So how do you build and maintain trust at scale?

My guest this week is Denise Chaffin, Founder of Top Source Talent and host of the Talking TA podcast. In our conversation, she shares how nearly four decades in recruiting have shaped her thinking on building trust at scale and ensuring technology strengthens relationships rather than undermines them.

In the interview, we discuss:

• The risk of transactional relationships
• Building and maintaining trust over time
• The limits of managing large networks
• How AI tools can support relationships
• Finding talent through unexpected connections
• Network Mapping
• Key skills to build trust and connection
• What the future looks like

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Many organizations are struggling with attrition, disengagement, and costly mis-hires that quietly destroy value. The real problem isn't finding talent, it's creating conditions where people can perform.

Research suggests that when people feel they belong, organizations see significant gains in productivity, retention, and innovation. Belonging can be measured, built into how work gets done, and connected directly to business outcomes.

So how can talent acquisition use belonging to change how it hires and the strategic value it delivers?

My guest this week is Eric Knauf, Founder and CEO of BelongHQ and author of The 56% Solution. In our conversation, he shares a practical framework for measuring belonging and explains how it could reshape TA's role in an AI-driven world.

In the interview, we discuss:

• The five pillars of belonging
• Measuring belonging against business outcomes
• Why workforce planning comes before EVP
• Breaking roles down to the task level
• Belonging as a talent differentiator
• Shifting TA from seats to strategy
• The hidden cost of untapped potential
• Building trust during the recruiting process
• What does the future look like

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AI skills are quickly becoming a baseline expectation in hiring, with more employers adding AI fluency to their job descriptions every month. Yet when you ask those same employers what AI fluency actually looks like for the vast majority of roles that aren't deeply technical, most struggle to answer. 

Universities still treat AI primarily as a cheating problem, restricting how students use it rather than helping them become fluent. So there's a growing gap between what the workplace demands and what education delivers. 

How do we define AI fluency in practical terms, and who should be leading that conversation?

My guest this week is Kathleen deLaski, Founder of the Education Design Lab and author of Who Needs College Anymore?. In our conversation, she shares what employers and students are revealing about AI readiness, and why the current approach risks failing a generation of new talent.

In the interview, we discuss:

• What is an AI-fluent workforce?
• Preparing learners for a new world of work
• Current student attitudes to AI
• Is the education system able to evolve quickly enough?
• Moving beyond prompts
• What replaces degrees in early-career hiring?
• Assessing human skills at scale
• Articulating what AI skills look like in your organization
• What does the future look like?

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AI is reshaping how work gets done, but the hiring process hasn't caught up. Employers are asking for AI skills they can't clearly define, while application volumes hit record levels. Resumes mean less than ever because candidates can now use AI to tailor them to any job in seconds, and traditional screening methods are struggling to keep pace.

At the same time, something more interesting is happening underneath all the noise. Candidates are often further ahead on AI than the companies hiring them. Forward-thinking employers are turning to work sampling, and rather than treating AI use as cheating, they're integrating it into the assessment as a necessary part of the process. Despite predictions that coding would be the first job to disappear, engineering hiring is actually up in some areas. 

So how should employers rethink assessment, upskilling, and what they look for in technical talent?

My guest this week is Amanda Richardson, CEO of CoderPad. In our conversation, Amanda shares what's really happening in technical hiring and where it's heading next.

In the interview, we discuss:

• What are AI skills?
• How is recruiting evolving?
• Previewing the actual work in the recruiting process
• AI-assisted assessment
• Upskilling, adaptability, and curiosity
• How is AI coding changing tech jobs?
• Candidates are ahead of employers on AI adoption.
• What does the future of jobs and hiring look like?
  

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Talent acquisition has always been built around the individual. Find the right person for the right role. But once someone joins a team, something far more complex takes over. How people combine matters as much as who they are on their own. Every person brings a unique mix of human qualities that affect how they work with others. Factor in all those qualities across all the possible ways a team could be put together, and the number of combinations quickly reaches into the trillions.

So how should employers think about team composition, and where does AI fit in as both a tool and a team member?

My guest this week is Dr. Bernhard Züenkeler, Co-Founder and Managing Director of Smycles. In our conversation, he explains how data can reveal hidden team potential, why AI should be treated as a team member rather than a replacement, and what hiring will look like when organizations start thinking in combinations rather than individuals.

In the interview, we discuss:

• The gap between hiring and performance
• The importance of team intelligence
• AI as the new team member
• The science behind team dynamics
• Why gut feel can never predict team performance
• Internal mobility and hidden talent
• Solving skill shortages differently
• What does the future of hiring look like?

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Every organization knows it needs to adopt AI. Far fewer have worked out how to bring their whole workforce along for the journey. Telling employees to use new tools rarely works, and many companies are stuck with pockets of enthusiastic early adopters alongside large groups who feel the pace of change is simply too much. Getting from scattered experimentation to genuine organization-wide adoption requires a very different approach, one where upskilling, learning culture, and the right mindset matter as much as the technology itself.

So what does it actually take to build a workforce that's ready for AI?

My guest this week, recorded at the recent Transform conference, is Katya Laviolette, Chief People Officer at 1Password. In our conversation, she shares how her team built an AI adoption strategy co-led by HR and the technology team, why soft skills now matter more than technical training, and how to cut through the noise when every vendor is selling AI.

In the interview, we discuss:

• Building organization-wide AI adoption
• The role of AI champions
• Balancing human and AI work
• Why curiosity and adaptability matter
• Upskilling versus hiring new talent
• Evolve, shift, and pivot.
• Evaluating AI tools and vendors in a noisy market
• Privacy and security considerations
• What the future looks like

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Round Up March  2026

If you’ve not listened to Roundup before, it’s a short review of the episodes that I’ve published in the last month to make sure you don’t miss out on the valuable insights that my guests are sharing.

This month Round UP returns to its live format, and this is a recording of my live conversation with Rhona Barnett-Pierce , Founder Workfluencer Media, about five of the episodes published in March 2026

Episodes featured in this Round Up:

Ep 774: Will Candidate AI Use Transform Recruiting?

Ep 775: What Makes An Excellent Workplace?

Ep 777: Why AI Needs To Drive Value Not Efficiency

Ep 778: What Makes Talent Acquisition Truly Strategic?

Ep 779: Can AI Democratize Hiring?

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Every platform, every feed, every channel is packed with posts and videos that increasingly look and sound like they were produced by the same machine. For employers trying to attract talent, corporate messaging already struggled to feel trustworthy, and AI-generated content has made the problem significantly worse. Candidates and consumers want to hear from real people, not polished brand accounts.

That's fuelled growing interest in employee-generated content, where real employees share their own authentic experiences of working at a company. The potential is enormous, but so is the risk of doing it badly and simply creating more forgettable noise. 

So how do employers tap into employee voices in a way that genuinely builds trust?

My guest this week is Rhona Barnett-Pierce, Founder of Workfluencer Media. In our conversation, she shares what separates effective employee content from scripted corporate messaging and how companies can get started.

In the interview, we discuss:

• Why employee-generated content builds trust
• How AI content is eroding authenticity
• Shifts in communication preferences
• Showing the work, not just the workplace
• The employers who are doing employee content well.
• Finding the existing content creators in your workforce.
• The future of content marketing

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Over the past year, AI features in recruiting tools have seen significant adoption.  But if you ask TA Teams whether AI has changed how they actually hire, most of them will say no. Individual productivity is up, but organizational transformation hasn't followed.

At the same time, AI tools on the candidate side are flooding employers with credible applications from candidates who may not be seriously interested. So what needs to shift for AI to genuinely transform recruiting for employers and candidates alike?

My guest this week is Nikos Moraitakis, Co-Founder and CEO of Workable. In our conversation, he shares why productivity gains haven't driven real change, how AI agents could take over sourcing and screening, why the recruiter role faces a dramatic shift, and what all this means for candidate experience.

In the interview, we discuss:

• Why AI adoption hasn't yet driven significant transformation
• AI-driven applications with low candidate intent
• How AI capabilities have advanced in the last few months
• Using agentic AI like a staffing agency
• AI automates tasks, not jobs.
• Why recruiters need to focus on the bottom of the funnel, not the top
• Trust, transparency, and human oversight
• What hiring looks like in the future

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I've recently returned from a long trip to Las Vegas, where I attended both the UNLEASH and Transform conferences. Unsurprisingly, AI dominated every session and every vendor booth at both events. The promise is huge, but the reality on the ground is a lot more complicated. Some teams are seeing genuine value from new tools. Others are finding that technology is creating as many problems as it solves. For many people, the sheer volume of options is making it harder, not easier, to know what to invest in. 

So what is actually happening with AI in talent acquisition right now?

My guest interview from UNLEASH is Meredith Johnson, Chief Product Officer at Greenhouse and my guest interview from Transform is Nicki Paterson, Chief Growth Officer at Solutions Driven. They share their honest perspectives on AI adoption, the human skills that matter more than ever, and what the future might look like.

In the interview, we discuss:

• AI hype versus the current reality on the ground
• The balance between humans and machines
• Trust, control, and transparency
• The shift from quantity and speed to quality and value in hiring
• Aligning HR and TA with critical business objectives
• The confusing vendor landscape
• What does the future look like?

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Application volumes have surged in recent years, and many talent acquisition teams are struggling to keep up. Candidates apply and disappear into a black hole, never hearing back, never getting a real chance to show what they can do. When volumes reach into the millions, the traditional recruiting model simply breaks. There aren't enough recruiters to give everyone a fair hearing.

Some organisations are now rethinking this entirely, using AI not to replace human decision-making, but to open the door wider than any human team ever could. So what does it actually look like when a company goes AI-first across every stage of hiring?

My guest this week is LJ Brock, Chief People Officer at Coinbase. In our conversation, he explains how they've deployed AI across five core areas of recruiting, why they now assess every candidate on AI fluency, their focus on talent density to constantly raise the quality bar, and what hiring will look like in the future.

In the interview, we discuss:

• The shift from volume to quality and value
• What does talent density mean at Coinbase?
• AI first recruiting to democratize access to the company
• Evaluating candidates on AI fluency
• Human connection in the hiring process
• Augmenting recruiters, not replacing them.
• Will all recruiting look like executive search in the future?
  

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A full transcript will appear here shortly.