Recruiting Future with Matt Alder - What's Next For Talent Acquisition, HR & Hiring?

AI is moving from a specialist technology to something employees in large parts of the organization are increasingly expected to be using. Skills, mindsets, and long-established habits are much harder to change than software, which is why meeting that expectation is proving difficult. If the challenge is mainly a human one, AI readiness is as much a matter for HR and talent leaders as for technology teams. So what does it take to get a workforce ready for AI, and what opportunity does that create for talent leaders? My guest this week is Dr. Michael Housman, Co-Founder and CEO of AI Performance Lab. Michael has spent 17 years building AI and machine learning platforms, and now helps leadership teams around the world adopt AI. In our conversation, he explains what the human aspect of AI readiness means in practice, why execution matters more than strategy, and why HR and talent leaders are well-placed to lead the change. In the interview, we discuss: What has changed since AI went mainstream, and what hasn't Why AI readiness is a question of mindset, culture, and skills Treating AI as a digital colleague rather than a tool Exponential innovation, flat adoption, and an hour a day of AI playtime The companies leading on AI are growing headcount, not cutting it Why a strategy deck is not the same as execution Deciding where humans stay in the loop, and the risk of skills atrophy Why this is a unique moment for HR and talent leaders Why experience and AI skills together are such a powerful combination What does the future look like when adoption can't keep pace with innovation? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

There is a lot of pressure on talent acquisition to adopt AI, and the discussion about how to do it tends to focus on tools and skills. With layoffs attributed to AI in the headlines, the people in TA teams have good reason to feel anxious about the technology they are being asked to use. That anxiety makes people less willing to experiment, and addressing it has less to do with the technology than with how leaders handle uncertainty. So what does it take to move a recruiting team from anxiety about AI to confidence in using it? My guest this week is Jennifer Rozon, Division President of McLean & Company, a global HR research and advisory firm whose recent research looks at leadership and AI transformation. In our conversation, Jennifer explains what is driving AI anxiety, how leaders can give their teams the confidence to experiment, and the risks of relying too heavily on AI and cutting entry-level roles. In the interview, we discuss: What is driving AI anxiety in the workforce? Why AI anxiety should not be mistaken for resistance to technology Leading through uncertainty when you don't have all the answers How leaders can give their teams the confidence to experiment How structures, incentives and culture can work against leaders What is cognitive debt and why does it matter? What happens to future leadership pipelines when entry-level roles disappear? Redesigning entry-level roles around the work AI creates Why current experience is becoming a less reliable basis for hiring and succession What does the future look like? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

The world of work is changing quickly, and the way people move between roles is changing with it. Hiring for senior positions looks very different from the way it did even five years ago, while many people still approach their own careers with instincts shaped by a market that no longer exists. What does it mean to manage a career well in this environment, and how do the people who navigate transitions successfully approach them differently? My guest this week is Kelly O. Kay, Global Managing Partner of the Enterprise Software and AI Practice at Heidrick & Struggles. Kelly has spent more than twenty years in executive search, and together with his longtime colleague Jeff Sanders he has just published Show Up to Win, a Harvard Business Review Press book on how leaders should manage their careers and navigate transitions. In our conversation, he explains how hiring at the top has changed, why career management needs to be a continuous and strategic activity, where AI does and doesn't fit into the process, and what people misunderstand about the way search firms work. In the interview, we discuss: How hiring at the most senior level has changed What the best leaders do to get the best roles Career management as a continuous process, not a response to wanting to move Quality of company, quality of role, quality of offer Showing them how you think via executive dialogue rather than question and answer What people misunderstand about how search firms work Using AI as an interview coach What does the future of leadership careers look like? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

AI is becoming more embedded across recruiting tools, but there is a meaningful difference between AI that automates workflows behind the scenes and AI that talks directly to candidates. When AI conducts the conversation, the stakes are higher; the first interaction shapes how candidates perceive the employer and the role. That is why many talent acquisition teams remain cautious about AI interviews, even as they adopt AI everywhere else. A growing number of enterprises are now running AI interviews at scale in high-volume hiring, and the data coming back on candidate experience and quality of hire improvements is difficult to ignore. So what does that evidence show, and what should it mean for how the industry thinks about AI in hiring? My guest this week is Dave Vu, Co-Founder and COO of Ribbon, who spent 15 years in talent and people leadership before co-founding the AI interview platform. In our conversation, Dave shares what enterprises are reporting from deploying AI interviews across thousands of candidates, how those candidates are responding, and what this could mean for the future of hiring. In the interview, we discuss: The shift from AI experimentation to enterprise deployment The difference between back-office AI and candidate-facing AI Moving from chatbots to natural conversations The impact on the candidate experience Building candidate trust and AI interviewing Improving speed, efficiency and quality of hire Detecting cheating and protecting interview integrity How will AI interviewing evolve over the next few years Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

If you've not listened to Round Up 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 my guest co-host Rhona Pierce from Workfluencer Media, about six of the episodes published during July and August 2026 Episodes featured in this Round Up: Ep 803: AI Native Recruiting Ep 807: Trust, Transparency And The AI Interview Ep 809: The Data Foundation For AI In Hiring Ep 812: Who Trains The Human In The Loop? ⁠⁠https://recruitingfuture.com/2026/07/ep-812-who-trains-the-human-in-the-loop/⁠⁠ Ep 816: Hiring For Judgment In The AI Era https://recruitingfuture.com/2026/08/ep-816-hiring-for-judgment-in-the-ai-era/ Ep 821: Why Every Employer Brand Sounds The Same https://recruitingfuture.com/2026/08/ep-821-why-every-employer-brand-sounds-the-same/

This is episode two of Decoding the C-Suite, a five part miniseries from Recruiting Future about how leadership really thinks about AI, recorded with the leadership team at SmartRecruiters seven months into their acquisition by SAP. The headlines about AI and the workforce are relentlessly grim: surveillance, layoffs, roles disappearing. Lehua Stonebraker, who leads the people function at SmartRecruiters, starts from a different place: naming the fear rather than managing around it. In this episode she explains how to build psychological safety when employees are scared to admit they use AI, why she believes the org chart is gone, how engagement went up during an acquisition, and a vision of a connected employee lifecycle that finally uses everything an organisation learns about its people.

There is growing consensus that AI is eroding the experience pathways organizations depend on to develop human judgment. Entry-level roles are shrinking, hands-on work is being automated, and fewer people are building the experience their businesses need. This is a well-documented challenge. What remains far less clear is what the talent strategy response should look like. Most skills systems today are built to track whether someone can execute a task, not how well they make decisions under ambiguity. If judgment is becoming the most important capability in the organization, recruiting, learning, and assessment all need recalibrating around it. So what does that recalibration look like in practice? My guest this week is Craig Friedman, author of Enterprise Skills Unlocked and Talent Transformation Leader at St. Charles Consulting Group. In our conversation, he explains why current skills infrastructure misses the capability that matters most, what work looks like when execution is automated, and how organizations can start building judgment into their talent strategy. In the interview, we discuss: What does enterprise AI adoption currently look like The long-term consequences of cutting entry-level jobs What does work look like when the automatable tasks are taken away? Why judgment is more important as a skill than ever before The difference between judgment and critical thinking Where does judgment fit into the skills infrastructure? How can TA teams hire for judgment? What does the future look like? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

Storytelling might be the most overused word in employer branding. Every company claims to tell stories, yet most of the content being produced sounds the same from one company to the next, and AI is about to make the problem significantly worse by flooding every channel with even more identikit messaging. At the same time, the science behind how stories work on the human brain is well established, comprehensive, and much harder to apply than most people realise. The employers who understand it are creating content that connects on an emotional level, while everyone else is just adding to the noise. So what separates real storytelling from content that just claims to be a story? My guest this week is Susanna Rantanen, founder of Employer Branding Agency Emine and author of the book Story-Driven Employer Branding. In our conversation, she shares why so much storytelling isn't storytelling at all, what the science tells us about how stories persuade, and how employers can use them to attract and retain the right people. In the interview, we discuss: The biggest current challenges in Employer Branding Why branding is a long-term play, not a short-term campaign The internal audience employers overlook Attracting the right people via meaning, relevance, and emotion Why most Employer Brand storytelling isn't storytelling at all The science of how stories work on the human brain How does proper storytelling work in practice The current and future impact of AI What does the future of employer branding look like?