Recruiting Future with Matt Alder

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, Tony 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.

Something has shifted in AI over the last few months. The pace of AI model updates keeps increasing, and strategies that made sense a few months ago are already out of date. New tools can take on long, complex pieces of work largely on their own, changing what's possible across hiring. For TA leaders, long-term planning has become almost impossible, while the recruiter's role itself is being rethought as candidates use AI just as actively as employers do. So what does effective TA leadership actually look like right now? My guest this week is Bryan Ackermann, Head of AI Strategy and Transformation at Korn Ferry. In our conversation, Bryan shares the changes he is seeing across the recruiting funnel and how organizations can build the resilience they need to keep pace. In the interview, we discuss: The accelerating pace of AI change Why AI literacy now matters everywhere Is candidate AI use cheating or demonstrating capability? The superpowered employee The evolving role of the recruiter Agents talking to agents Where human moments still matter Resilience and shorter planning horizons Advice to TA Leaders What does the future look like? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

We live in a world where recruiters can connect with thousands of people with a single click. LinkedIn, CRMs, and AI tools all promise to manage relationships at a scale unimaginable a generation ago.  The challenge is that genuine trust doesn't scale automatically. When interactions become automated and transactional, the very thing that makes recruiting work starts to break down. People still hire people they trust, and the best referrals still come through relationships, not algorithms. So how do you build and maintain trust at scale? My guest this week is Denise Chaffin, Founder of Top Source Talent and host of the Talking TA podcast. In our conversation, she shares how nearly four decades in recruiting have shaped her thinking on building trust at scale and ensuring technology strengthens relationships rather than undermines them. In the interview, we discuss: The risk of transactional relationships Building and maintaining trust over time The limits of managing large networks How AI tools can support relationships Finding talent through unexpected connections Network Mapping Key skills to build trust and connection What the future looks like Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

Many organizations are struggling with attrition, disengagement, and costly mis-hires that quietly destroy value. The real problem isn't finding talent, it's creating conditions where people can perform. Research suggests that when people feel they belong, organizations see significant gains in productivity, retention, and innovation. Belonging can be measured, built into how work gets done, and connected directly to business outcomes. So how can talent acquisition use belonging to change how it hires and the strategic value it delivers? My guest this week is Eric Knauf, Founder and CEO of BelongHQ and author of The 56% Solution. In our conversation, he shares a practical framework for measuring belonging and explains how it could reshape TA's role in an AI-driven world. In the interview, we discuss: The five pillars of belonging Measuring belonging against business outcomes Why workforce planning comes before EVP Breaking roles down to the task level Belonging as a talent differentiator Shifting TA from seats to strategy The hidden cost of untapped potential Building trust during the recruiting process What does the future look like Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

AI skills are quickly becoming a baseline expectation in hiring, with more employers adding AI fluency to their job descriptions every month. Yet when you ask those same employers what AI fluency actually looks like for the vast majority of roles that aren't deeply technical, most struggle to answer.  Universities still treat AI primarily as a cheating problem, restricting how students use it rather than helping them become fluent. So there's a growing gap between what the workplace demands and what education delivers.  How do we define AI fluency in practical terms, and who should be leading that conversation? My guest this week is Kathleen deLaski, Founder of the Education Design Lab and author of Who Needs College Anymore?. In our conversation, she shares what employers and students are revealing about AI readiness, and why the current approach risks failing a generation of new talent. In the interview, we discuss: What is an AI-fluent workforce? Preparing learners for a new world of work Current student attitudes to AI Is the education system able to evolve quickly enough? Moving beyond prompts What replaces degrees in early-career hiring? Assessing human skills at scale Articulating what AI skills look like in your organization What does the future look like? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

AI is reshaping how work gets done, but the hiring process hasn't caught up. Employers are asking for AI skills they can't clearly define, while application volumes hit record levels. Resumes mean less than ever because candidates can now use AI to tailor them to any job in seconds, and traditional screening methods are struggling to keep pace. At the same time, something more interesting is happening underneath all the noise. Candidates are often further ahead on AI than the companies hiring them. Forward-thinking employers are turning to work sampling, and rather than treating AI use as cheating, they're integrating it into the assessment as a necessary part of the process. Despite predictions that coding would be the first job to disappear, engineering hiring is actually up in some areas.  So how should employers rethink assessment, upskilling, and what they look for in technical talent? My guest this week is Amanda Richardson, CEO of CoderPad. In our conversation, Amanda shares what's really happening in technical hiring and where it's heading next. In the interview, we discuss: What are AI skills? How is recruiting evolving? Previewing the actual work in the recruiting process AI-assisted assessment Upskilling, adaptability, and curiosity How is AI coding changing tech jobs? Candidates are ahead of employers on AI adoption. What does the future of jobs and hiring look like? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

Talent acquisition has always been built around the individual. Find the right person for the right role. But once someone joins a team, something far more complex takes over. How people combine matters as much as who they are on their own. Every person brings a unique mix of human qualities that affect how they work with others. Factor in all those qualities across all the possible ways a team could be put together, and the number of combinations quickly reaches into the trillions. So how should employers think about team composition, and where does AI fit in as both a tool and a team member? My guest this week is Dr. Bernhard Züenkeler, Co-Founder and Managing Director of Smycles. In our conversation, he explains how data can reveal hidden team potential, why AI should be treated as a team member rather than a replacement, and what hiring will look like when organizations start thinking in combinations rather than individuals. In the interview, we discuss: The gap between hiring and performance The importance of team intelligence AI as the new team member The science behind team dynamics Why gut feel can never predict team performance Internal mobility and hidden talent Solving skill shortages differently What does the future of hiring look like? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

Every organization knows it needs to adopt AI. Far fewer have worked out how to bring their whole workforce along for the journey. Telling employees to use new tools rarely works, and many companies are stuck with pockets of enthusiastic early adopters alongside large groups who feel the pace of change is simply too much. Getting from scattered experimentation to genuine organization-wide adoption requires a very different approach, one where upskilling, learning culture, and the right mindset matter as much as the technology itself. So what does it actually take to build a workforce that's ready for AI? My guest this week, recorded at the recent Transform conference, is Katya Laviolette, Chief People Officer at 1Password. In our conversation, she shares how her team built an AI adoption strategy co-led by HR and the technology team, why soft skills now matter more than technical training, and how to cut through the noise when every vendor is selling AI. In the interview, we discuss: Building organization-wide AI adoption The role of AI champions Balancing human and AI work Why curiosity and adaptability matter Upskilling versus hiring new talent Evolve, shift, and pivot. Evaluating AI tools and vendors in a noisy market Privacy and security considerations What the future looks like Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

Round Up March  2026 If you've not listened to Roundup before, it's a short review of the episodes that I've published in the last month to make sure you don't miss out on the valuable insights that my guests are sharing. This month Round UP returns to its live format, and this is a recording of my live conversation with Rhona Barnett-Pierce , Founder Workfluencer Media, about five of the episodes published in March 2026 Episodes featured in this Round Up: Ep 774: Will Candidate AI Use Transform Recruiting? Ep 775: What Makes An Excellent Workplace? Ep 777: Why AI Needs To Drive Value Not Efficiency Ep 778: What Makes Talent Acquisition Truly Strategic? Ep 779: Can AI Democratize Hiring? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

Every platform, every feed, every channel is packed with posts and videos that increasingly look and sound like they were produced by the same machine. For employers trying to attract talent, corporate messaging already struggled to feel trustworthy, and AI-generated content has made the problem significantly worse. Candidates and consumers want to hear from real people, not polished brand accounts. That's fuelled growing interest in employee-generated content, where real employees share their own authentic experiences of working at a company. The potential is enormous, but so is the risk of doing it badly and simply creating more forgettable noise.  So how do employers tap into employee voices in a way that genuinely builds trust? My guest this week is Rhona Barnett-Pierce, Founder of Workfluencer Media. In our conversation, she shares what separates effective employee content from scripted corporate messaging and how companies can get started. In the interview, we discuss: Why employee-generated content builds trust How AI content is eroding authenticity Shifts in communication preferences Showing the work, not just the workplace The employers who are doing employee content well. Finding the existing content creators in your workforce. The future of content marketing Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

Over the past year, AI features in recruiting tools have seen significant adoption.  But if you ask TA Teams whether AI has changed how they actually hire, most of them will say no. Individual productivity is up, but organizational transformation hasn't followed. At the same time, AI tools on the candidate side are flooding employers with credible applications from candidates who may not be seriously interested. So what needs to shift for AI to genuinely transform recruiting for employers and candidates alike? My guest this week is Nikos Moraitakis, Co-Founder and CEO of Workable. In our conversation, he shares why productivity gains haven't driven real change, how AI agents could take over sourcing and screening, why the recruiter role faces a dramatic shift, and what all this means for candidate experience. In the interview, we discuss: Why AI adoption hasn't yet driven significant transformation AI-driven applications with low candidate intent How AI capabilities have advanced in the last few months Using agentic AI like a staffing agency AI automates tasks, not jobs. Why recruiters need to focus on the bottom of the funnel, not the top Trust, transparency, and human oversight What hiring looks like in the future Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

I've recently returned from a long trip to Las Vegas, where I attended both the UNLEASH and Transform conferences. Unsurprisingly, AI dominated every session and every vendor booth at both events. The promise is huge, but the reality on the ground is a lot more complicated. Some teams are seeing genuine value from new tools. Others are finding that technology is creating as many problems as it solves. For many people, the sheer volume of options is making it harder, not easier, to know what to invest in.  So what is actually happening with AI in talent acquisition right now? My guest interview from UNLEASH is Meredith Johnson, Chief Product Officer at Greenhouse and my guest interview from Transform is Nicki Paterson, Chief Growth Officer at Solutions Driven. They share their honest perspectives on AI adoption, the human skills that matter more than ever, and what the future might look like. In the interview, we discuss: AI hype versus the current reality on the ground The balance between humans and machines Trust, control, and transparency The shift from quantity and speed to quality and value in hiring Aligning HR and TA with critical business objectives The confusing vendor landscape What does the future look like? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

Application volumes have surged in recent years, and many talent acquisition teams are struggling to keep up. Candidates apply and disappear into a black hole, never hearing back, never getting a real chance to show what they can do. When volumes reach into the millions, the traditional recruiting model simply breaks. There aren't enough recruiters to give everyone a fair hearing. Some organisations are now rethinking this entirely, using AI not to replace human decision-making, but to open the door wider than any human team ever could. So what does it actually look like when a company goes AI-first across every stage of hiring? My guest this week is LJ Brock, Chief People Officer at Coinbase. In our conversation, he explains how they've deployed AI across five core areas of recruiting, why they now assess every candidate on AI fluency, their focus on talent density to constantly raise the quality bar, and what hiring will look like in the future. In the interview, we discuss: The shift from volume to quality and value What does talent density mean at Coinbase? AI first recruiting to democratize access to the company Evaluating candidates on AI fluency Human connection in the hiring process Augmenting recruiters, not replacing them. Will all recruiting look like executive search in the future? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify. A full transcript will appear here shortly.

The role of talent acquisition is changing fast. AI and automation are transforming what's possible, while CFOs and CEOs are demanding a different kind of conversation. They want to understand the value talent acquisition creates for the business and how it delivers returns that directly tie to strategic goals. The old transactional language of efficiency no longer cuts it. TA leaders who can connect what they do to business impact are the ones building a successful case for investment. The problem is, with vendor capabilities increasingly overlapping, knowing where to put that investment has never been harder. So what does it take to reposition talent acquisition as a truly strategic function? My guest this week is Jason Cerrato, SVP of Global Talent at Amentum. In our conversation, he shares how the TA conversation has evolved, why business acumen matters more than ever, and how to cut through the technology noise to make the right investment decisions. In the interview, we discuss: How the TA conversation has changed Telling a story of impact, not efficiency Speaking the language of the CFO The new criteria for tech investment Moving from a cost centre to a strategic function Changing the way organizations think about talent. Balancing AI with human connection Navigating similarity and sameness in tech products Choosing the right fit, not just the best tool The future of talent acquisition Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

We're at a fork in the road for how companies adopt AI. Some are taking shortcuts, slashing entry-level roles and chasing efficiency savings. Others are slowing down to ask a harder question: how does this technology actually create new value? The data suggests that many companies are choosing the wrong path, using AI as a scapegoat for cost-cutting that is really caused by other business challenges. The consequences for their talent pipelines, skills development, and long-term competitiveness could be severe. So what separates organisations that get AI right from those that don't, and what does this mean for talent acquisition? My guest this week is Kelly Monahan, founder of Beyond the Desk. and a highly experienced labour economist who advises organisations on building genuine AI capability. In our conversation, she explains what most companies are getting wrong, the skills that actually matter, and the implications for talent acquisition. In the interview, we discuss: How are skills evolving? Why AI is being used as a scapegoat The real cost of cutting entry-level roles Three skills that define AI readiness Protecting high-value human touchpoints Buy or build? Using technology strategically AI for organizational value, not efficiency shortcuts Data privacy and compliance risks Developing the skills and mindset needed to future-proof your career What does the future look like? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.