Ep 836: Continuous Improvement In TA

TA leaders usually know what needs to improve in their function; the hard part is deciding what to do first. AI is adding to the confusion, with an ever expanding vendor landscape and technology that is getting stronger for many use cases while remaining weak in others. So what do the teams that keep improving do differently? My guest this week is Tony de Graaf, Co-Founder of the Recruiting Excellence Foundation, whose global benchmark measures the maturity of TA functions around the world against a single framework. In our conversation, Tony shares what the benchmark says TA does well and where it falls short, why no region is as far behind as it thinks, how to make sense of the AI vendor landscape, and the one question high-performing teams use to decide what to improve next. https://www.linkedin.com/in/graaftony/ https://recruiting-excellence.org In the interview, we discuss: Building a global benchmark of TA maturity What TA functions already do well, and where the gaps are Why so many regions believe they are behind the others Narrow AI tools and the time they do and don't save Do AI tools pay for themselves? Making sense of a confusing vendor landscape Personal AI agents and what they really cost The one test high-performing TA teams apply to every improvement Why improvement is continuous, not a project What does the future look like? Take the Recruiting Excellence assessment and contribute to the next global benchmark: https://mattalder.me/2027 Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

I recorded four conversations at UNLEASH World in Paris in October, and there was one theme that kept coming up in all of them. My interviewees argued that AI is starting to redesign the work itself, and with it how organizations are built, how roles are defined, and how people are hired. Most of them build HR technology for a living, so they see further ahead than most employers, but they obviously have a stake in the future they describe. So what does all of this mean for how companies are run and how they hire? My guests are Mervyn Dinnen, an analyst and author on HR and talent trends; Allyn Bailey, Senior Director of Corporate Narrative and Executive Communications at SmartRecruiters; Ronni Zehavi, Co-Founder and CEO of HiBob; and Dalit Brosh, Co-Founder and CEO of Glimpse. In our conversations, they discuss why talent acquisition may stop being a separate function, what it takes to put an agent on the org chart, how to assess people for roles that have not been created yet, and why the experience people have at work still decides whether they join and stay. In the interview, we discuss: The missing debate about what should stay human and what should go to AI Does talent acquisition still make sense as a separate function? Hiring people into the company rather than into a role The widening gap between forward-looking and transactional organizations Four dimensions of AI change, from employee psychology to government regulation Agents on the org chart and what it takes to onboard, govern and review them Is the era of the large enterprise over? Assessing what people are capable of rather than what they have done Measuring learning agility and adaptability to AI What will the big HR narrative of 2027 be? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

There is no shortage of predictions about AI in HR and hiring at the moment. Most of them come from analysts, vendors and commentators looking in from the outside. Far more useful, and much harder to come by, is the perspective of someone actually doing the work, running the transformation and making these changes inside their own organization. That is exactly why I wanted to talk to this week's guest. My guest is Vic Akosile, Head of AI Transformation and People Strategy at Cloudflare, where he also serves as Chief of Staff to the Chief People Officer. He sent me a set of predictions for AI in HR in 2027, and they make a great framework for understanding what is really changing and what it means for the people doing this work. In our conversation, Vic talks me through those predictions and what each one looks like in practice. In the interview, we discuss Vic's predictions, including: More HR teams will build and maintain their own AI agents and applications HR functions will appoint internal AI product leaders Businesses will judge AI on much more than time saved or cost avoided Employees who get faster with AI will hide that they are using it Work design will come before headcount planning Recruiters will use live exercises and work samples to assess judgment What the longer-term future holds beyond 2027 Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

AI can automate a large and growing share of the recruiting process, and within a few years it may be capable of handling almost all of it. For employers, the question is what AI should be doing in hiring, not simply what it could, and that means deciding where people still need to be involved. Human in the loop is the standard response, but it can amount to little more than a person reviewing and approving what the AI recommends. A recruiter in that position becomes a validator rather than a decision maker, and a process built that way can feel just as impersonal as one with no human in it at all. Human in the loop is not the same as human agency, where recruiters apply their own judgment, context, and knowledge of the business to the decision. So how should employers decide not just where people belong in the process, but what they are there to do? My guest this week is Rob Devlin, founder of Devlin Talent.. In our conversation, Rob explains why the problem has to come before the technology, what human agency looks like in practice, what recruiters should do with the time AI gives back, and how choosing which parts of hiring to keep human can become a competitive advantage. In the interview, we discuss: Starting with the problem, not the product What should AI be doing, rather than what could it do? Why AI won't fix a broken process Using AI to improve the intake meeting Human in the loop versus human agency What to deliberately choose not to automate Six lenses for looking at any AI decision Where human conversations create competitive advantage What TA leaders can build themselves before buying new technology Why the AI decisions being made today are designing the future of work 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 Jim Miller VP of People & Talent at Ashby about four of the episodes published in September 2026 Episodes featured in this Round Up: Ep 823: How AI Is Disrupting Entry Level Jobs Ep 824: Is AI Creating Talent Debt?  Ep 825: The Real Risks Of Candidate Fraud  Ep 827: Agent To Agent Recruiting     

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.

Redundancies have become a constant feature of the talent market. AI is taking a lot of the blame, but the drivers behind this are much broader. Jobs and skills are changing faster than most organizations can keep track of and the conventional response is to restructure the workforce and then hire in the new skills that are needed. That approach relies on a ready supply of perfectly qualified candidates, and in a fast-moving skills market those candidates are increasingly hard to find. It also assumes that employers already have a clear view of the skills and potential within their existing workforce, which is rarely the case. So what does a smarter approach to restructuring look like? My guest this week is JC Townend, President of The Adecco Group for the UK and Ireland and CEO of LHH, the Adecco Group business that supports individuals through redundancy. In the UK alone, LHH works with more than 20,000 people a year who have been made redundant, which gives JC a rare view of both the decisions employers are making and where the people affected end up next. In our conversation, she explains what is really driving the current wave of restructuring, why the financial case for replacing people rather than redeploying them has changed, and how the best employers are rethinking workforce planning. In the interview, we discuss: How the pattern of restructuring has changed over the last eight years What is really driving the current wave of redundancies AI, automation and the skills mismatch that goes well beyond them Why companies understand skills within teams but not across them The employers letting people go and then rehiring for similar skills Why the perfectly qualified external candidate is getting harder to find Changing how internal moves are perceived and helping people sell their transferable skills Agile workforce planning and a matrix of opportunities rather than a single career ladder Five careers in a lifetime, all at the same company, and what the future looks like Connect with JC on LinkedIn: https://www.linkedin.com/in/jeannetownend/ Read the 2026 LHH Career Redeployment and Outplacement Trends Report: https://www.lhh.com/en-gb/insights/the-mobility-breakdown 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.

TA leaders have to keep delivering for the business while they use AI to transform how hiring works. At RecFest USA in Nashville, AI was the main topic of conversation, although the people I spoke to talked about much more than the technology. So where should TA leaders be focusing their attention? I recorded seven short interviews at the event, and they fall into three themes. Those themes are the value that talent acquisition brings to the business, the risks that employers now have to manage, and what comes next for hiring. My guests are Jamie Leonard, Founder of RecFest; Stef Nikitas, Director of Talent Acquisition at Ace Hardware; Julia Levy, a former Fortune 500 talent acquisition executive; Jim Stroud, Head of Market Strategy and Industry Engagement at ProvenBase; Lorna Erickson, Co-Founder of Expert Interviewers; Mark Chaffey, Co-Founder and CEO of hackajob, the company behind Archer; and Ben Russell, Co-Founder and CCO of SonicJobs. In our conversations, they discuss who should own quality of hire, how employers are responding to legal risk and candidate fraud, and how AI is changing the way candidates and employers find each other. In the interview, we discuss: The growing conversation about how TA aligns with business goals Who should own quality of hire and how should it be measured? The compliance and legal pitfalls around AI and pay transparency How to check for candidate fraud without making the process harder for real candidates The lack of trust between candidates and recruiters How job seekers are using large language models to look for work What generative engine optimization means for employers Is agent-to-agent hiring the future of talent acquisition? 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.