Hiring processes are full of design choices that nobody ever questions. Requirements that sound reasonable but aren't defined. Formats that have stayed the same for decades. Onboarding systems built for one type of learner. Talented people are being screened out, not because they can't do the job, but because of how the process itself is designed.

These aren't people failures; they're design failures that quietly exclude the people organisations most need. So how do we actually design hiring in a way that works for everyone?

My guest this week is Theo Smith, author of the new book Designed for Humans: Rethinking Work in the Age of AI. In our conversation, he shares practical ways to spot and fix the system design flaws hiding in plain sight across the hiring process.

In the interview, we discuss:

• Why people aren't always the problem
• The hidden barriers in job ads
• Probation periods as red flags
• Why structured interviews still fail
• How people mask gaps at work
• AI is accelerating flawed system design.
• Onboarding as a critical failure point
• Designing workplaces for humans

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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 Ritu Mohanka, CEO at Vonq, about six of the episodes published in February 2026

Episodes featured in this Round Up:

Ep 766 How TA Proves Its Business Impact

Ep 767: Inside EY’s Talent Strategy for AI and the Future

Ep 769: Managing Risk In Talent Acquisition

Ep 770: The Science of Better Hiring

Ep 771 Recruiting At The Speed Of AI

Ep 772: Surfing The AI Tsunami

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Attracting talent gets all the headlines, but retention is where the real competitive advantage lives. In a market where top performers are constantly being approached by competitors and salary expectations keep rising, holding on to your best people has never been harder.

At the same time, the rapid pace of AI and automation means the skills companies need are shifting faster than ever, making internal development and mobility just as critical as external hiring.

So how do you build a workplace where people genuinely want to stay and grow?

My guests this week are Annika in der Beek, Chief People Officer, and Giovanni Di Felice, Director of Talent Acquisition at Statista. In our conversation, they share the science-backed framework behind what makes an excellent employer and explain how hiring and retention are becoming inseparable parts of the same strategy.

In the interview, we discuss:

• Hiring challenges in AI and tech
• Encouraging candidates to use AI
• Why retention has become critical
• Measuring what makes an excellent employer
• Autonomy, competence, and relatedness at work
• The power of honest feedback
• Internal mobility and career development
• TA as a strategic business partner
• What does the future look like?

Learn more about The Excellent Workplace Rating.

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Many talent acquisition teams are dealing with surging application volumes right now, and AI is a major factor. Candidates are using it to apply faster, at a greater scale, and with more targeted information than ever before. The instinct has been to treat candidate AI use as noise, something to filter out or push back on. That response misses the long-term implications entirely.

AI isn't just a tool for corporate hiring teams anymore. Candidates have access to the same technology, and platforms are emerging specifically to help them use it strategically. The innovation this unlocks could drive more change in recruiting than anything employers are currently investing in.

So what is candidate-side AI actually capable of, and are talent acquisition teams thinking seriously enough about where this leads?

My guest this week is Sam Wright, Head Of Career Strategy at Huntr, a data-backed job search platform. In our conversation, he shares what candidates are really doing with AI and what the data reveals about where this is heading.

In the interview, we discuss:

• The job market from a candidate's perspective

• How the job search is changing

• Declaring a truce in the AI arms race

• Candidate-driven disruption and innovation in hiring

• Ethics and responsibility

• The importance of human judgement

• What does the future look like?

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For years, recruitment marketing strategies have been built around a familiar set of rules: optimize your career site, rank well in search results, and ensure candidates can find you. But those rules were written for a world where Google was the gateway.

That world is changing. Candidates are increasingly turning to LLMs like ChatGPT and Claude to research potential employers, asking detailed, conversational questions about culture, benefits, and working environment. And the way those tools surface information is fundamentally different from traditional search. The content that performs well in Google often doesn't translate, and organizations that have invested heavily in their employer brand discovery may be largely invisible in this new landscape.

So what does it take to show up when candidates are searching in LLMs?

My guest this week is Graham Thornton, President of Consulting and Growth at Talivity. In our conversation, he explains how candidate discovery is changing, why existing SEO thinking doesn't apply, and what organizations need to do differently.

In the interview, we discuss:

• How AI is disrupting recruitment marketing
• The new uneven playing field
• Content and context
• The importance of structure and specificity
• How third-party content is influencing discovery
• How are job seekers now searching?
• New ways of measuring ROI
• What will the future look like?

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AI transformation is accelerating, and for many organizations, the biggest risk isn't the technology itself; it's getting their strategic response wrong. Rush in without a framework, and you can destroy culture, trust, and capability. Hold back waiting for certainty, and more agile competitors will overtake you. Talent leaders are caught between these two failure modes with no clear playbook, and the pressure is intensifying by the week. So what does a disciplined, structured approach to navigating AI disruption actually look like in practice, and what role should talent and HR be playing?

My guest this week is Jagrity Singh, a transformation leader who specializes in integrating AI-driven talent strategies with process excellence disciplines. In our conversation, she introduces a model for understanding where work sits between fully human and fully automated, and explains why the organizations that win will be those that learn to surf the wave rather than get crushed by it.

In the interview, we discuss:

• Differences in AI approaches between Europe, the Middle East, and North America.
• The impact of AI on jobs and what approach employers should be taking

• AI is an HR problem, not an IT problem.
• Why CHROs need to orchestrate human and AI workforces
• Strategic workforce planning
• What should be automated and what shouldn’t
• Advice to talent leaders
• What does the future look like?
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Recruiting has always been shaped by the time and resources available. Resumes are short because recruiters only have a finite amount of time to read them. Interview shortlists are small because hiring managers can only meet so many candidates. The whole funnel narrows because no team can fully evaluate everyone who applies. None of these are strategic choices, they're simply workarounds for human capacity.

Now AI agents can screen hundreds of candidates in a matter of hours, run outside business hours, and deliver structured evidence for recruiters to review. The data coming back is already challenging assumptions about how these processes should work, while the growing influence of AI on who progresses through the hiring process makes questions around ethics, fairness, and regulatory compliance impossible to ignore.

So how should TA leaders rearchitect their processes while keeping them responsible?

My guest this week is Sachit Kamat, Chief Product Officer at Eightfold. In our conversation, Sachit shares early data from AI interviewing at scale and explains why it's time to reimagine recruiting processes as the traditional constraints around time and resources start to fall away.

In the interview, we discuss:

• Lifting capacity limitations in recruiting
• The impact of AI interviewing on the candidate experience
• What humans do better than technology
• Radically improving the candidate experience.
• Building agent scale processes
• The first steps to transforming recruiting
• Regulation and responsibility
• Could the time to hire be reduced to less than 1 hour?
• What does the future look like?

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Hiring should be about finding the right person. Too often, though, the tools and methods organizations use actually work against them. Job postings filter candidates out for lacking skills they could easily and quickly learn. Competency checklists based on someone else's philosophy of what leadership looks like rather than what actually works inside their organization. Assessment tools that aren't scientifically validated or that screen for average profiles when the role needs something entirely different.

The funnel narrows before employers even realize it. And when a poor fit does get through, the individual can spend months or years struggling against expectations that were never clearly defined.

So how should organizations rethink the way they assess and select talent?

My guest this week is Dr. Stephanie Puckett, founder of SynergyMind Consulting. In our conversation, she draws on 20 years of experience in organizational psychology to reveal where hiring processes quietly break down and the implications for both employers and employees when they do.

In the interview, we discuss:

• The most common mistakes employers make in hiring

• Unintentional restriction of talent pools

• Skill and competency transfer

• The danger of using tools with no scientific validation

• The critical role of talent acquisition teams

• Data science versus psychology

• Finding confirmation bias in big datasets

• The importance of realistic job previews

• How will hiring develop in the next 2 to 3 years
  

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The pressure on talent functions right now is intense. Budgets are tight, teams are stretched, and the mandate to do more with less has pushed many organizations to automate at speed without stopping to redesign what they were automating.  These automated decisions are attracting real legal and regulatory attention. Actions previously seen as simple process steps are now potentially being viewed from a legal perspective as consequential decisions.

At the same time, there's a growing recognition that AI could be truly catalytic, forcing the kind of fundamental change that talent functions have needed for years. 

So how do leaders navigate the constraints while seizing that opportunity?

My guest this week is Kyle Lagunas, Founder of Kyle and Co. In our conversation, Kyle unpacks what defensibility really means in practice, why talent teams need to shift from risk avoidance to risk readiness, and how AI is catalyzing long-overdue transformation.

In the interview, we discuss:

• Credibility under constraint

• Risk averse or risk avoidance?

• What does defensibility look like?

• The AI balance between execution and judgement

• Human-in-the-loop needs to be designed, not assumed.

• Are we holding machines to a higher standard than we hold humans to?

• The importance of rigour in pilot programs

• Building AI literacy

• What does the future look like?

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AI tools are changing the pace at which organizations filter and rank candidates. However, matching someone to a job description and actually predicting whether they'll perform well in the role are two very different things. Most hiring processes have never been validated against real performance outcomes, and organizations often don't have a clear, measurable definition of what success looks like in a role. Without that foundation, even the most sophisticated AI is just automating something that was never evidence-based in the first place. 

So what would it actually take to build hiring processes that genuinely predict performance?

My guest this week is Jennifer Yugo, Managing Director and owner of Corvirtus, and an organizational psychologist specializing in evidence-based hiring. In our conversation, she explains the science behind predicting job performance and why most hiring processes are far from where they need to be.

In the interview, we discuss:

• Matching candidates vs predicting performance
• Why most hiring lacks evidence
• Defining what success really looks like and identifying performance indicators
• Do some AI hiring tools stand up to scrutiny?
• The risks of automating bad decisions
• Questions TA leaders should ask vendors
• Are we going to see a reckoning for hiring technology?
• What might the future look like?

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The assurance and audit profession is facing a talent crisis. Fewer graduates are choosing it as a career, and the perception of what auditors actually do hasn't kept pace with reality. At the same time, AI is fundamentally reshaping the work itself, automating repetitive tasks and opening up entirely new service areas around cyber risk and sustainability. The profession needs different skills, different mindsets, and a completely different value proposition for the next generation of talent.

So how do you transform a workforce of over a hundred thousand people while simultaneously making the profession attractive to a generation that wants purpose, flexibility, and career agility?

My guest this week is Sandra Oliver, Global Assurance Talent Leader at EY. In our conversation, she shares how EY is reskilling auditors at scale, bridging generational divides around technology adoption, and repositioning audit careers as a launchpad for business leadership.

In the interview, we discuss:

• Attracting Gen Z to the audit profession
• AI's impact on day-to-day audit work
• Upskilling 130,000 professionals in AI
• Bridging the generational technology gap
• Reverse mentoring between junior and senior staff.
• Purpose and meaningful work as talent drivers
• How will audit careers evolve over the next five years?

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