Explorez tous les épisodes du podcast 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.

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.

Recruiting is generating more activity than ever and less connection. Candidates are using AI to produce polished applications at scale, employers are using AI to screen and reach out at scale, and the result is a level of noise that is eroding trust on both sides. More automation applied to the same processes will only make this worse. Solving it means rethinking how matching works, with depth of understanding on both sides and transparency and fairness designed in from the start. So what does that look like in practice? My guest this week is Matt Wilson, Co-founder and CEO of Jack and Jill, whose AI agents work on both sides of the hiring market. In our conversation, Matt shares why supercharging existing processes deepens the noise problem, how transparency and independent auditing build trust in AI matching, and where human judgment remains essential. In the interview, we discuss: Why job hunting is still an inefficient, luck-based process How AI is supercharging broken processes and creating noise on both sides of hiring Building trust in agentic driven processes Bias, fairness, and transparency Challenging deep-seated beliefs about how recruiting gets done Where human judgment remains essential in the hiring process How Jack and Jill manage their own hiring process What does agent-to-agent recruiting mean for the future of hiring? 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.

Remote hiring, freely available deepfake tools and harvested identities have created an opportunity that organized criminals are now taking seriously. State-backed operations are training workers to apply for remote roles using stolen credentials and proxy interviewers. The aim is the salary and access to source code, customer data and intellectual property once they are inside. Recruiters are the ones meeting these people first, and in most organizations they are assessing them with a background check and their own judgment while IT, InfoSec and legal are rarely involved. So how seriously should employers be treating this, and what does a credible response look like? My guest this week is Lauren Furey, Principal Product Manager at Proof, where she leads product work on candidate fraud and identity verification. In our conversation, Lauren explains how these attacks work, where hiring processes are most exposed, and what TA teams can do about it. In the interview, we discuss: Bots, deepfakes, identity harvesting and proxy interviewers The criminal motivations behind state-backed infiltration Why the background check is no longer enough on its own How much recruiters overestimate their ability to spot a fake Why remote hiring created the gaps bad actors exploit Building identity continuity through the hiring process Making fraud prevention a shared responsibility with IT and InfoSec The candidate experience trade-off and where to place verification Verifiable credentials and protecting candidates' own identities Practical first steps and what does the future look like? https://www.linkedin.com/in/laurennfurey/ https://www.proof.com 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/

Inside most organizations, the pressure has shifted from proving that AI works to showing what it is worth in cost, productivity and headcount. Some workforce plans are now being decided on that basis before anyone has looked closely at how the work is done. The organizations getting the most from AI are treating it as a question of work design rather than technology. So what does designing work around AI involve, and what does it cost the organizations that skip that step? My guest this week is Matt Campbell, Managing Director at Alvarez & Marsal, where he leads the Talent, Organization & People practice and advises organizations on workforce strategy and organization design. In our conversation, he explains why most AI pilots produce an inconclusive result, a five-stage model of AI's impact on work, the ways organizations misread their own people, and why cutting too far, too fast creates a talent debt. In the interview, we discuss: - Why most AI pilots are designed to prove the wrong thing - Who owns AI? - Why big tech's approach to AI and headcount is the wrong template for everyone else - The difference between a job and a role - The five A's: avoid, assist, augment, automate and autonomous - How to put numbers against cost, productivity and capacity - The four things organizations most often get wrong - Why unauthorized AI use gives employees the benefit and the organization the risk - Talent debt and the cost of cutting too far, too fast - Are you designing work around AI, and what does the future look like?

In software development, AI tools now write much of the code, and at a growing number of organizations junior developers are no longer doing that work themselves. Tech is where the impact on a first job is clearest, and likely a preview of what other industries will see next. When the tools handle the technical work, what is left requires judgment, collaboration and communication, capabilities that take much longer to develop. That changes how people are prepared for work and what employers should be hiring for. What should the pathway into a tech career look like now? My guest this week is Reuben Ogbonna, Co-Founder and Executive Director of The Marcy Lab School, a one-year alternative to college in Brooklyn that prepares young adults for careers in tech. In our conversation, he explains why the traditional college model is falling behind, what people are still needed for when AI writes the code, and how employers should rethink entry-level hiring. In the interview, we discuss: The impact AI is having on first jobs The rising bar of expectations for early careers What skills should students now be learning Why developing judgment matters and why it is difficult to teach The difference between tasks and jobs How do educators keep up with changing needs? Learning that has to mimic the real workplace How should employers redesign entry-level hiring? What does the future look like, and how might AI drive job creation? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

Hi there, welcome to episode 822 of Recruiting Future with me, Matt Alder. Employer branding teams are still under sustained pressure. Budgets have shrunk and headcount has been reduced across many organizations, even when the hiring the business needs has become more specific and more critical. Despite all of the cuts, some employer brand leaders are still winning investment and influence. What sets them apart is how closely their work connects to what the business is trying to achieve and how effectively they communicate its impact. So what does it take to make employer branding matter to the business? My guest this week is Stephen Quinn, CEO of Atomic, an insight-led agency working with employer brand leaders at some of the world's largest organizations. In our conversation, Stephen shares what the most effective employer brand leaders do differently, which metrics carry weight with the business, and how to plan employer branding for the long term. In the interview, we discuss: Trends and challenges in Employer Branding What separates the most successful employer brand leaders Attaching Employer Branding to the critical needs of the employer Where should employer branding sit in the organization? Building relationships across the business Measuring and reporting on impact and ROI via the right metrics Long-term strategy thinking rather than short-term campaign thinking What does the future of Employer Branding look like Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

Employer messaging has a sameness problem. Candidates researching potential employers find the same values, the same mission statements, and the same well-meaning phrases wherever they look, which makes choosing between companies harder than it should be. The upside is a genuine opportunity. Standing out is no longer about outspending the competition; it comes from understanding what your organization offers that others don't, and the work of finding and proving that difference is now within reach of employers of any size. So how do you uncover what genuinely makes you different? My guest this week is James Ellis, founder of Employer Brand Labs and author of several books on employer branding. James has spent his career arguing that every company, whatever its size, can compete for talent by leaning into what makes it different. In our conversation, he shares why difference matters more than ever, why real proof beats nice-sounding claims, and where employers should start. In the interview, we discuss: Why so many employers sound identical What scraping every Fortune 500 career site reveals Why playing it safe has become the riskiest strategy The opportunity for employers outside the Fortune 500 The chicken soup story and the power of proof How AI changes the economics of employer brand work Finding evidence in the material you already have Why differentiation takes courage as well as insight What does the future look like? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

The gap between claiming to be strategic and actually operating strategically has real consequences, and nowhere are they clearer than at the top of HR. CHRO turnover is unusually high at the moment, and it also spikes sharply in the first year under a new CEO. A change at the top usually brings a new thesis about what the business needs, and what the CEO needs from HR shifts with it. Many CHROs find themselves running a system built for the previous mandate, and by the time the gap becomes visible, trust has already eroded. The problem is structural rather than personal, which means it can be fixed. So what separates the HR leaders who thrive in the role from those who don't? My guest this week is Jackson O. Lynch, founder of Talent Sherpa and a former CHRO who works with CEOs, CHROs, and boards on connecting talent systems to business strategy. In our conversation, Jackson shares why mandate misalignment drives so much churn at the top of HR, what operating at the top level means in practice, and why AI is making the redesign of work urgent. In the interview, we discuss: Why is CHRO turnover so high? Mandate misalignment and the conversation that rarely happens What does strategic HR look like in practice? Systems for transformation versus systems for stability Looking at business strategy through the talent lens Business logic versus compliance logic in the C-suite The trust issue Why AI is forcing a rethink of how work is designed Can HR take this opportunity for reinvention, and what does the future look like? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

The job of Chief People Officer has never been more demanding, and the way organizations decide who gets it is changing fast. Appointment volumes have fallen sharply, boards are rethinking what they value in an HR leader, and the profile of the people winning the top seats looks different from even two years ago. Experience of having done the job before is no longer the deciding factor it once was, which changes the calculation for everyone with ambitions on the role. So what are boards really looking for when they appoint a Chief People Officer? My guest this week is Olivia Sharp, a Partner at executive search firm Eton Bridge Partners, where she leads searches for Chief People Officers and board-level appointments and heads the firm's research into CPO hiring globally. In our conversation, she shares what the data reveals about experience versus potential, the skills that now define the role, and how TA leaders can position themselves for the top job. In the interview, we discuss: The fundamental shifts in what organizations value when hiring Chief People Officers Why boards are taking calculated risks on potential rather than buying proven experience What the appointment data means for first-time CPO candidates The leadership qualities that now matter more than HR expertise Where the traditional HR career path falls short The commercial capability gap in HR development How TA leaders can position themselves for the top job The swing back to external hiring and why new doesn't mean radical What will the Chief People Officer role look like in the future? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

Skills have been on the HR agenda for decades, but they rarely became the basis for real decisions; frameworks took so long to build that the business had moved on before they were finished. What's different now is that AI agents are starting to handle work that used to require a person, and that changes the question employers need to ask. It's no longer just about who to hire; it's about whether the work needs a human at all. When you can map work to the skills it requires, you have a basis for deciding what stays with people and what moves to an agent. Making that shift isn't straightforward, though; it raises questions about what HR itself needs to look like and what capabilities the function needs to develop. So what does it take to make skills the basis for deciding how work gets done? My guest this week is Ciara Harrington, Chief People Officer at Skillsoft. In our conversation, Ciara shares how Skillsoft is rethinking which work needs a person, why HR has to become more technical to lead that conversation, and what happens when you add "bot" to your talent strategy. In the interview, we discuss: How is AI changing the way we think about skills? Build, buy, borrow, bot Helping leaders understand what work could be done differently Tasks, skills, jobs, and units of work How understanding skills underpins this transformation AI can be more expensive than humans Building an effective governance model Hiring technical skills into HR and connecting the data Critical human skills and why they need to be developed faster What does the future look like? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

This is the final episode 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. Three years into the AI boom, the marketing noise has never been louder. Everything is AI-powered and every vendor makes the same claims. In the final episode, Steve Hardy, who leads marketing at SmartRecruiters, is unusually candid about all of it: why he tells his own sales team to stop demoing, what he calls AI washing, why buyers should start with business priorities rather than features, and what actually builds trust with buyers and candidates alike. The series closes with the question that ran through every conversation: what does good leadership look like in an AI-driven world?

This is episode four 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. AI is moving faster than any buyer can absorb, and that creates a genuine design problem: build for the boldest customers and you lose everyone else, build for the cautious and you fall behind. Shefali Netke, VP of Product Design at SmartRecruiters, lives in that tension every day. She explains how to design for a spectrum of readiness rather than an average user, why she refuses to keep designing for the old world, how her team builds AI fluency, and what it takes to merge two design cultures into one team.

The organisations genuinely driving AI change in talent all have one thing in common: alignment with the C-suite. Decoding the C-Suite is a five part miniseries from Recruiting Future exploring how leadership really thinks about AI. Recorded over one day with the leadership team at SmartRecruiters, seven months into their acquisition by SAP, the series unpacks AI through five lenses: the thesis, the people, the money, the product and the market. If you want to understand the conversations happening around your own leadership table, and how to win them, this series is for you. In the opening episode, the tables are turned as SmartRecruiters' Allyn Bailey interviews Matt on the future of talent acquisition. Matt shares his honest assessment of the outdated stories the industry keeps telling itself, why mental models matter more than systems, how candidates are already breaking recruiting, and a prediction about AI agents talking to AI agents that he's prepared to be held to. It sets the agenda for the four leadership conversations that follow.

This is episode three 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. If you've ever struggled to get AI investment signed off, this episode is for you. Tom DiDesidero, CFO at SmartRecruiters, explains exactly what he wants to see in a business case, why he backs short, measurable pilots over big commitments, and how to bring evidence rather than instinct. He also lifts the lid on the real economics of AI, from unpredictable inference costs to gross margins far below anything the SaaS world is used to, and makes a prediction about how the AI and SaaS worlds inevitably come together.

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.

Cybersecurity is one of the hardest markets to hire in, and a lot of the difficulty comes from how companies approach the process. Candidates are still being filtered on degrees, previous employers, and years of experience- signals that are particularly weak in a field where the best work is confidential, and skills need updating constantly. Good people are getting screened out, and what looks like a talent shortage can often be a matching problem. So, what changes when companies stop filtering on the usual proxies and start hiring on what candidates can actually do? My guest this week is Laurent Halimi, CEO and founder of Cyberr.ai, a professional network for cybersecurity professionals. In our conversation, Laurent explains why the skills shortage in cybersecurity is only half the truth, where the bias in hiring really comes from, and what it takes to judge candidates on skills that you can actually verify. In the interview, we discuss: How AI is changing what cybersecurity professionals do and the new roles it is creating A real skill gap at the senior level and a matching problem everywhere else The certification race and why it is losing relevance Why hiring in cybersecurity is different from other technical fields Trust, stale skills, and work that stays invisible Where the bias in hiring algorithms really comes from Practical steps for judging candidates on verifiable skills Anonymous applications and giving candidates control of their profiles Will skills finally beat pedigree, and what does the future look like? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

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.

AI adoption is accelerating, but for most organisations it is still ad hoc. Tools are bought reactively, budgets keep growing, and few leaders can say with confidence what is being used, what is working, or what return they are getting. Some companies are already going further, cutting roles on the assumption that machines can simply take over tasks from people. What rarely gets examined is what those decisions do to the people who remain, the culture they work in, and the customers they serve. So what do organisations need to understand about how work happens before they let AI reshape it? My guest this week is Sam Naficy, Chairman and CEO of Prodoscore, a data analytics company that studies employee engagement, productivity, and collaboration in large enterprises. In our conversation, Sam shares what his data reveals about AI use and productivity, the cultural consequences of automating roles, and why visibility into work has to come before automation. In the interview, we discuss: Why most organisations are still in the early stages of AI adoption The growing gap between AI spending and visibility into what is being used What the data shows about heavy AI users and productivity Why some employees adopt AI faster than others The unforeseen impact of automation on workplace culture What happens to the teams that remain when their AI replaces their colleagues Stress-testing workforce changes before making them The line between visibility and surveillance What does the future of work look like?

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?

AI has disrupted the dynamics of hiring. Candidates can now apply to hundreds of roles in a single click, while legal and regulatory constraints limit how far recruiters can use AI to review what comes in. The result is a flood of applications that keeps growing because so little of it gets properly reviewed. With the inbound recruiting channel under this much pressure, sourcing offers a different equation; it's a channel where employers set the quality bar themselves, and AI has fundamentally changed what it can deliver. The implications reach beyond pipeline quality. New approaches to sourcing could transform the candidate experience and open career paths that traditional hiring would never have surfaced. So what does it take to make sourcing a genuine strategic priority? My guest this week is David Paffenholz, Co-Founder and CEO of Juicebox. In our conversation David explains what is driving the inbound challenges, how AI is transforming what sourcing can do, why every role could get the executive search treatment, and what this could all mean for candidates and their careers. In the interview, we discuss: The paradox of record application volumes and persistent skill shortages Why candidates are using AI more effectively than employers How bulk applying is creating a self-reinforcing loop that is breaking inbound The business case for making sourcing a strategic priority Exponentially improving the candidate experience Treating every role like an executive search Human judgment and the changing role of the recruiter How skills-based matching could unlock career mobility and evidence that it is already happening What does the future look like? Juicebox https://juicebox.ai/ David on LinkedIn https://www.linkedin.com/in/david-paffenholz/

For the last few years, most corporate conversations about AI have been about efficiency, automating tasks, and reducing headcount. That conversation is now starting to change, with more attention on what constant AI use is doing to the human capabilities organizations depend on. Judgment sits at the center of this. It develops through years of hands-on experience, often in exactly the kind of junior work AI is now taking over. With many employers also hiring fewer entry-level people, developing the leaders of the future is becoming a serious challenge. So how do organizations use AI to amplify human capability rather than erode it? My guest this week is Johan Roos, Professor in Strategy at Hult International Business School and author of the new book Human Magic: Leading with Wisdom in an Age of Algorithms. In our conversation, Johan shares why the AI conversation is changing, the human capabilities that now matter most, and the practical choices employers face in developing judgment for the future. In the interview, we discuss: The dual mood of AI anxiety and excitement Moving the AI conversation beyond efficiency Amplification versus erosion of human capability The five human capabilities that matter most Why judgment comes from experience The risks of cutting entry-level hiring Thinking in tasks, not people Building an agentic workforce without cutting jobs Early warning indicators of talent risk Bionic collaboration and what the future looks like https://itunes.apple.com/podcast/recruiting-future-podcast/id963756980?mt=2&ls=1 https://open.spotify.com/show/4u3Gl0l4pGBtIHOJZjLTrx?si=49641466567e44d6 https://www.linkedin.com/in/drjohanroos/ A full transcript will appear here shortly.

TA leaders are under real pressure to keep up with AI, new tools, and what they think other employers are doing. In that rush, a lot of functions are spending heavily on new technology without first understanding whether their existing processes are working, only to find the real problem was something no platform could have fixed. Getting this right means doing the internal work first, auditing what's already in place, and being honest about organizational readiness. So what does it take to turn the lens inward before looking outward? My guest this week is Jalpa Trivedi, an experienced Global Head of TA who has built and centralized TA functions across more than 30 countries. In our conversation, she shares why the internal audit matters more than the technology choice, how to build TA foundations that hold across different markets, and how to approach AI adoption with the governance it requires. In the interview, we discuss: The questions TA leaders aren't asking about their own function. Investing in technology that solves the wrong problem -The 80/20 approach to centralizing TA across markets -Building an EVP on evidence, not assumptions -What persuades leadership to back a TA investment -Why the biggest AI risk isn't falling behind -Five data privacy questions to ask before signing with an AI vendor -Where the dividing line falls between AI and human judgment -What does the future look like? A full transcript will appear here shortly. Follow This Podcast on Apple Podcasts Follow this Podcast on Spotify

AI has been applied to almost every step of the hiring process. Sourcing, screening, assessments, interviews; each has its own tools, and many of them are effective. For many organizations, though, the gains from optimizing individual stages are flattening out. Hiring quality is shaped by the entire journey, not by any single step, and most hiring technology was never built to connect those steps. The focus is shifting toward connecting the whole process so that each stage learns from the others and improves over time. So what does it take to move from optimizing separate steps to building connected intelligence across the hiring process? My guest this week is Ben Chino, Co-founder and CPO of Maki. In our conversation, Ben explains why improving hiring one step at a time has hit its limits, what end-to-end hiring intelligence looks like in practice, and what it means for recruiters and candidates. In the interview, we discuss: Why optimizing individual hiring steps with AI has hit diminishing returns The difference between a system of record and a system of intelligence How a connected hiring process improves decision-making at every stage Where the ATS fits in the next generation of hiring technology Why human judgment in hiring is less consistent than most people think Freeing recruiters for better judgment and more time with candidates Turning 800,000 applications into a real candidate experience Why adopting AI in hiring is an organizational change challenge, not a technology decision What does the future of hiring look like? https://www.linkedin.com/in/ben-chino/

Agentic AI is only as useful as the data it can access, and getting that foundation right is proving to be the harder half of the work. Years of mergers, acquisitions, and local decision-making have left many talent operations running on data and processes that were never meant to work together, and no amount of AI on top will fix what lies beneath. Some organizations are now rethinking their technology strategy in light of that problem. So what does getting AI-ready actually involve, and what does it change about the decisions you make? My guest this week is Lia Manafova, Talent Technology Strategy Lead at Sanofi, a global pharmaceutical company hiring at scale across more than 70 countries. In our conversation, Lia explains why the data foundation must come first, what an anchor product strategy looks like in practice, and what she has learned about making technology stick. In the interview, we discuss: Why AI readiness starts with data, not AI Building a bridge between the business and the digital team The challenge of constant transformation and change fatigue What is an anchor product strategy? How the Workday, Paradox and HiredScore acquisitions changed the options Best-of-breed or a single source of truth? Keeping recruiters in one system rather than three Piloting with the people who will use it every day The case for keeping the semi-automated option Building an ROI story the business understands What does the future look like?

Innovation in recruiting is hard. TA leaders are experts at running their operations, but improving them in a structured way is a different discipline, and the AI revolution has made it one that no one can avoid. Before any function can innovate, though, it has to know where it is starting from, and that is where benchmarking becomes critical. Recent research from the Recruiting Excellence Foundation, which has assessed the maturity of hundreds of TA teams worldwide, reveals that TA teams are struggling to move from operational to strategic. So how should TA leaders get started? My guest this week is Toni de Graaf, Co-Founder of the Recruiting Excellence Foundation. In our conversation, Toni shares what the global benchmark reveals, why so many teams are stuck in operational mode, and how to prioritize the improvements that matter most. In the interview, we discuss: Benchmarking TA maturity across the globe The most surprising insight from the results The two areas where TA teams struggle most The difference between an operational and a strategic function The impact of AI AI and broken processes Resource, capacity and value Knowing your starting point What does the future look like? Take the recruiting excellence assessment

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 Ben Chino, Co-Founder and Chief Product Officer of Maki People, about five of the episodes published in May and June 2026 Episodes featured in this Round Up: Ep 790: Rethinking Work In The Age Of AI Ep 791: Making Agentic AI Work For HR & Talent Ep 797: Hiring The Humans Behind The Robots Ep 799: Growing the Talent You Can't Hire Ep 800: Will AI Break Recruiting? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

Application volumes are climbing fast, and AI has made it far easier for candidates to produce a strong-looking resume. For talent teams trying to give every candidate a fair hearing, the traditional model of recruiting is starting to break down. Some employers are now handing the first conversation to an AI voice agent, and that raises some obvious concerns. Does automating the first step strip out the human connection that recruiting depends on? The teams doing this well are finding the answer isn't what a lot of recruiters expect, and that getting it right depends as much on how openly it's done as on the technology itself. So what does it look like in practice? My guests this week are Jean-Baptiste Anne, Global Director of Talent Acquisition at Mirakl, and Anneliese Muscari, their Head of AMER and Global Go To Market talent acquisition. In our conversation, they share why they made the change, how candidates have responded, and what it means for the future of the recruiter role In the interview, we discuss: Managing unprecedented application volume The growing limitations of resumes How do you give every applicant a fair chance and a great candidate experience? Handing the first conversation to an AI voice agent Moving from skepticism to trust Publishing AI guidelines for candidates How candidates have responded Keeping humans in charge of every decision What does the future look like? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

Over the last year, I have been using AI to develop a searchable archive of the content in every episode of Recruiting Future, 3 million words from over a decade of unscripted conversations with practitioners and thought leaders across talent acquisition. James Whitelock, host of The Marketing Rules Podcast, has been doing the same thing with his own archive of more than 200 episodes over seven years.  Between us, we now have over a thousand real conversations we can interrogate for trends, and the picture that emerges is an industry caught in familiar tensions: fighting to prove its strategic value, grappling with AI that moves faster than it can be adopted, and trying to figure out which parts of hiring should stay fundamentally human.  So what do years of real conversations reveal about where talent acquisition actually stands?   In my conversation with James, we compare what our respective archives reveal about TA's shifting identity, the real pace of AI's change, and the tensions the industry keeps returning to. In the interview, we discuss: Using AI to turn podcast archives into industry intelligence TA's journey from growth engine to cost center and back again How the AI conversation has shifted over time Adaptability as the critical skill for TA Is TA becoming a marketing function? Standing out when AI content all sounds the same Ring-fencing the parts of hiring that should stay human Bias in humans and bias in AI What does the future look like? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

The talent market is sending mixed signals. Employers insist they can't find the people they need, while experienced, capable candidates say they are applying into a void and hearing nothing back. Both are describing the same market, so something in the middle is failing. A lot of recruiting technology was built to handle volume, to move large numbers of applicants through a process quickly. What it struggles to do is read signal, to interpret whether someone actually has the judgment and context to solve the problem a business has. So how do we fix this problem, and will AI give us the solution? My guest this week is James Gardner, a talent acquisition and transformation leader who has spent over twenty years building and scaling talent functions. In our conversation, he shares what his own data-driven job search revealed about the market, why volume systems and signal systems pull in opposite directions, and how AI could either fix the problem or make it considerably worse. In the interview, we discuss: What's really happening on both sides of the talent market Why the market isn't short of talent; it's short of signal. Running a job search as a data funnel Why silence, not rejection, is the real problem Why volume systems and signal systems contradict each other Where AI screening still can't read potential Applying AI to a broken process just makes it fail faster. Moving TA from a service function to a commercial lever Owning the outcome, not just the shortlist. What does the future look like? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify

As AI reshapes how work gets done, the most valuable thing a person can bring to their job isn’t recent task experience; it is the depth of judgment, sector knowledge, and decision-making that takes years to build. That is precisely what AI augments rather than replaces. However, in a cautious hiring market, recency is being given overinflated importance, and a large pool of deeply experienced professionals is being filtered out because they have a gap on their resume. These are people with the experience and maturity, and strong appetite for engaging with new technology that the AI era needs. So why are employers overlooking this talent, and how should TA leaders rethink their hiring strategies to fix this My guest this week is Hazel Little, CEO of Career Returners. In our conversation, Hazel explains what the data reveals about the returner experience in 2026, why deep experience and judgment matter more than recency in an AI-augmented workplace, and shares some practical advice on making hiring more effective. In the interview, we discuss: How the landscape for career returners has worsened in the last year The unique benefits returners can bring to organizations. Why there is still so much stigma around career breaks and resume gaps How the hiring process amplifies the confidence gap The importance of potential over experience in a fast-changing world of work Why the human judgment needed to work with AI comes from experience The skills shortage hiding in plain sight Building potential rather than buying experience Screening and the hiring manager mindset What TA needs to do differently to harness this valuable talent pool. Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

AI offers a genuine opportunity to reinvent talent acquisition, but not many employers have gone beyond targeting incremental improvements in speed and efficiency. The ones who are truly using AI to be transformational are doing something fundamentally different. It takes a real commitment to experimentation, a clear definition of what AI fluency means, and a willingness to redesign hiring from scratch.  So what does that shift actually look like in practice? My guest this week is Tracy St. Dic, Global Head of Talent at Zapier, where going AI-native is a company-wide mission. In our conversation, Tracy shares how Zapier is redefining AI fluency, redesigning the hiring process from the ground up, and rethinking what the recruiter role looks like in an AI native world. In the interview, we discuss: What is an AI Native company? The difference between AI adoption and AI transformation What is AI fluency? A mindset of experimentation, curiosity, and discernment Upskilling the TA Team Psychological safety and protected time The impact of implementing an AI interviewer and the diminishing importance of the resume Fraud versus cheating versus just using the available tools What is true transformation in recruiting, and what does the future look like Follow this podcast on Apple Podcasts. Follow this podcast on Spotify

The way people look for work is changing fast. A growing number of job seekers now begin by using tools like ChatGPT, asking questions in plain language about roles, salaries, and what it's actually like to work for a company. It is a very different starting point from typing a job title into a search box and scrolling through pages of aggregator links. At a time when employers are drowning in low-intent applications, something interesting is happening at the other end. Candidates who find roles through AI search arrive with real context about the company, the role, and why it fits their life. So how can employers make the most of this new world of job search? My guest this week is Ben Russell, Co-founder at SonicJobs. In our conversation, Ben explains how AI-driven job search is developing, what it means for candidate intent, and why he thinks this moment could rebuild trust between employers and job seekers. In the interview, we discuss: The role LLMs are now playing in the job search. Changes in job seeker behaviour Lessons from the rise of Google Building apps in ChatGPT Implicit and explicit discovery The implications of conversational search Delivering well-informed, high-intent applicants How employers can own their own brand What does the future of the job search look like? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify. A full transcript will appear here shortly.

A growing number of organizations are rushing to put AI to work, often announcing themselves as AI-first before working out what that actually means. What many are finding is that AI tends to surface whatever was already underneath. Where the data is patchy, the content conflicting, and no one quite owns the end-to-end process, the technology exposes all of it rather than fixing any of it. At the same time, AI is starting to reshape work itself, raising hard questions about which tasks remain genuinely human and what HR and TA roles will look like on the other side.  So what does it take to build foundations solid enough to make these tools deliver? My guest this week is Mark Stelzner, founder and managing principal at IA. In our conversation, Mark explains what it really takes to make AI work in the people function. In the interview, we discuss: What are the driving forces and catalysts for transformation? How AI amplifies rather than fixes existing problems What does AI first actually mean? Re-inventing processes in large complex organizations AI’s impact on work Displaced skills, amplified skills, and uniquely human skills Turning capacity into new value The impact of transformation on people and culture The new role of the CHRO Follow this podcast on Apple Podcasts. Follow this podcast on Spotify. A full transcript will appear here shortly.

Recruiting has always had an innovation problem, and the AI revolution has brought it to a fork in the road. Will AI facilitate a revolution in hiring that drives more value than we have seen in 200 years or will it finally break recruiting as we’ve always known it.  In this special 800th episode of Recruiting Future, Matt Alder tells a story that brings together Cornish Tin miners migrating to Mexico in the 1820, a letter Leonardo Da Vinci wrote to the Duke of Milan in 1492, the rise of AI and long-standing problems with have with innovating how we recruit talent.  How can we use AI to solve age old problems, what are the risk involved and how should TA Leaders be preparing their teams?  In the episode Matt discusses: How modern-day recruiting has been inherited and never designed The similarities between recruiting today and recruiting 200 years ago Case studies illustrating the huge amount of value AI can bring in hiring Three big risks The fork in the road AI has brought us to A framework for AI Readiness Winding roads and jagged frontiers How we can build the future Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

In some industries, aging workforces and deepening skill shortages mean companies can no longer rely on hiring the experienced workers they need. The only realistic option is to grow their own, and that puts apprenticeship schemes right at the centre of workforce planning. Running a programme at that scale raises questions that go well beyond recruiting. Culture shapes whether people stay, mentoring determines whether skills actually transfer, and long-term success often depends on governments understanding how to direct support towards the future talent that industries actually need.  So what makes an apprenticeship scheme genuinely effective for high-skilled talent, and what has to be in place around it to make it work? My guest this week is David Dart, Chief People Officer at Caliber Holdings. In our conversation, David shares what he's learned building a skilled-talent pipeline at scale. In the interview, we discuss: The unique talent challenges in recruiting auto body technicians Skills shortages and an aging workforce Culture and retention The importance of mentoring The impact of AI on jobs The importance of trades careers and the need for government support What does the future look like? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify. A full transcript will appear here shortly.

In frontline industries, if you can't hire fast enough, the operation stops. A restaurant that can't fill shifts doesn't open. A delivery company that can't onboard drivers loses customers overnight. This constant pressure has pushed frontline employers to adopt AI and automation faster and further than any other area of recruiting. Frontline hiring is now where some of the most advanced AI-driven recruiting is happening. Agents are screening candidates, running compliance, and managing entire workflows. Things that felt theoretical months ago are already working.  So what can every employer learn about AI agents, candidate trust, and the balance between humans and automation? My guest this week is Salim Jernite, Chief Product Officer at Fountain. In our conversation, Salim explains how the rapid pace of AI is transforming frontline operations and shares lessons that apply far beyond frontline hiring. In the interview, we discuss: Current challenges in frontline hiring Why speed is the key metric What advantages does AI bring? The importance of candidate experience and building trust AI Orcestration with “Cue” Keeping up with the relentless pace of AI development The balance between humans and automation What does the future look like? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

The race to develop humanoid robots that can work alongside people in factories, warehouses and retail environments is attracting billions in investment. The talent powering this revolution is in critically short supply. Specialist AI researchers, robotics engineers, and machine learning experts are being sought by every company in the sector, from global tech giants to ambitious startups. So, in this environment of talent scarcity, how much does the human side of recruiting matter? My guest this week is Kathrin Selezneva, Talent Acquisition Lead at Humanoid. In our conversation, she shares her experience building a hiring function from scratch in one of the most competitive talent markets in the world and explains why, as AI transforms everything around it, the human skills of recruiting have never mattered more. In the interview, we discuss: Building a TA function from zero Recruiting the world’s most challenging talent market Building trust with the most passive of candidates Why mission sells when salary can't The vital importance of human recruiters Relationship building and strategic thinking Why talent should determine geography in global hiring What does the future look like? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

Employee engagement remains one of the most talked-about challenges in the world of work. Year after year, the data tells the same story: levels barely shift, no matter what organizations try. The usual response is to focus on what happens once people are already in the door, but the results rarely change. At the same time, AI is reshaping roles and expectations, making employees question their value in ways that weren't there before. So what if the real engagement problem starts in the hiring process itself? My guest this week is Dr. Roz Cohen, Chief People Officer and author of “The Engagement Dilemma”. In our conversation, she explains why there are three distinct types of engagement, how outdated job descriptions undermine them, and what hiring teams should do differently to build belonging from the start. In the interview, we discuss: Why engagement levels haven't shifted Three types of employee engagement The role of TA in employee engagement Reassessing roles before recruiting Hiring for attributes and behaviours Onboarding for connection and belonging Identity beyond surface characteristics What does the future look like? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify. A full transcript will appear here shortly.

In frontline retail hiring, speed is everything. If the process is too slow, candidates take offers elsewhere, and stores are short-staffed, hurting both service and revenue. AI-powered automation is now helping some organizations close that gap, cutting hiring times, saving thousands of hours, and driving measurable financial value for the business.  The organizations seeing real results started with the problem, not the technology, because layering AI onto a process that isn't working only makes things worse. They also had to answer a question that rarely gets asked: how quick is too quick, and when does speed start to feel impersonal? The goal isn't to remove humans from the hiring process. It's to remove the noise so candidates reach the right people faster. My guests this week are Stef Nikitas, Director of Talent Acquisition at Ace Hardware, and Rachel Allen, Senior Director of Talent Acquisition at 7-Eleven. In our conversation, they share how they transformed frontline hiring with AI, the results it delivered, and where they chose to keep humans firmly in the process. In the interview, we discuss: Why speed matters in frontline hiring The danger of automating broken processes Leading with the problem, not the technology How quick is too quick? What remains human and why How automation improves the candidate experience Time savings and measurable business value Advice for TA on change management What does the future look like Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

When organizations hire thousands of frontline workers, delivering a personal candidate experience becomes almost impossible. Recruiters spend all of their time answering calls, responding to messages, and running through the same screening questions over and over. There is little time left for the conversations that actually matter. Meanwhile, candidates want speed, flexibility, and a process that respects their time, including outside business hours. So how can AI solve this? My guests this week are Jeroen Klerkx, People Operations Leader at Picnic, and Bill Fischer, CTO at VONQ. In our conversation, recorded live at HR Tech Europe, they share what happened when Picnic gave candidates the choice of a human or AI screening call, the surprising feedback they received, and how they built 10 years of recruiting knowledge into an AI agent that frees up time for their recruiters to have more valuable conversations. In the interview, we discuss: Picnic’s unique approach to candidate experience The current market challenges Building an AI recruiter Closely monitoring candidate sentiment and responding to their feedback. Overcoming the considerable technical challenges How recruiters responded to automation and how their role is developing Managing candidate expectations around AI What does the future look like for AI in TA Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

HR is at a pivotal moment. AI has shifted the conversation in a way nothing else has in years, the demands on the function are growing faster than its capacity to respond, and the questions being asked of it are bigger than they have ever been. The opportunity is significant, but so is the gap between where HR is and where it needs to be. So what does it actually take for HR to step into this moment? In this episode, recorded at HR Tech Europe in Amsterdam, I'm joined by two guests with strong views on what's holding the function back and what good looks like. Anna Carlsson, an HR tech analyst based in Stockholm, shares what she's seeing across the Nordic market and why culture and infrastructure matter more than the technology itself. Nazhttps://www.linkedin.com/in/nazim-ünlü-0774b714/im Ünlü, a Global HRD and HR transformation leader, then joins me to talk about why HR is more needed than ever and the strategic shift the function has to make to stay relevant. Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.https://open.spotify.com/show/4u3Gl0l4pGBtIHOJZjLTrx?si=49641466567e44d6

Talent acquisition is sitting in a strange place right now. AI is in every conversation, but the work of actually hiring people is getting harder rather than easier. Application volumes are swinging in unpredictable ways, the workforce itself is changing shape, and the reality on the ground is some distance from the hype. So what is actually going on in talent acquisition right now? In this episode, recorded at HR Tech Europe in Amsterdam, I'm joined by two guests who have spent decades watching this industry evolve.  Wolfgang Brickwedde from the Institute for Competitive Recruiting shares what his research is telling him about the market employers are navigating and where vendors are still getting it wrong.  Mervyn Dinnen then joins me to talk about the reality behind the AI hype and how the multigenerational workforce is reshaping the world of work. Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

The real value of AI agents in HR comes from connecting them to work across the employee lifecycle, not from deploying them on individual tasks. That's where most large organisations are getting stuck. Working in a fully agentic way means dealing with different systems and different data sources that often have no shared foundation. The result is fragmented experiences for employees and managers, with the end-to-end potential remaining out of reach. Getting there requires some serious work in data governance, process design, and integration, the kind of foundational work that rarely gets mentioned at industry conferences. So what needs to be in place before AI agents can work at enterprise scale? My guest this week is Melissa Shelley Höjwall, Global HR Technology Lead at H&M Group. In our conversation, which we recorded live at HR Tech Europe, she explains what it takes to build a connected AI architecture across HR and why many companies are undermining their own progress. In the interview, we discuss: The approach to Agentic AI in HR at H&M From niche agents to connected architecture Process automation design and date integration The role of data governance Adoption in the enterprise Shadow AI and over-governance Why cutting jobs isn’t the way to get true value from AI New roles for HR professionals Breaking the silos in the Talent function What to focus on for the future Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

We're living through one of the most consequential shifts in how work gets done. AI is everywhere in headlines and vendor pitches, but the reality inside organisations is far more nuanced than the noise suggests. Personal adoption is running well ahead of how companies are embedding the technology into actual workflows. Demographic changes continue to tighten labour supply, and the HR tech vendor landscape is consolidating and expanding all at once, leaving buyers uncertain about where to invest.  So how should HR leaders be thinking about technology, workforce design, and the role they need to play in shaping what work actually becomes? Recorded live at HR Tech Europe, my guest this week is Stacey Harris, Chief Research Officer at Sapient Insights Group. Stacey runs the longest-running HR systems survey in the market, and we discuss what her data shows about where things are heading. In the interview, we discuss: How AI differs from past tech shifts Layoffs and the cost of AI investment The gap between personal and corporate AI use Why bring your own AI matters Making sense of the vendor landscape The Platform Cluster Model  Demographics and labour supply pressures From workforce planning to workforce architecting How HR's role needs to change What does the future look like Take part in The 29th Annual HR Systems Survey Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.