Recruiting Future with Matt Alder - What's Next For Talent Acquisition, HR & Hiring?
Published by Matt Alder
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Talent acquisition is undergoing unprecedented disruption as AI, economic uncertainty, and the ever-shortening lifespan of skills radically reshape recruiting. On Recruiting Future, Matt Alder explores this evolving landscape, using insightful interviews with transformational TA practitioners and forward-thinking experts to spark your imagination and provide the insights you need to shape the future of talent acquisition in your organization. Each episode explores topics such as AI, recruiting automation, recruitment marketing, employer branding, skills-based hiring, assessment, candidate experience, DEI, internal mobility, and the transformation of TA teams. Recruiting Future is an essential resource for everyone involved in hiring. Matt Alder is a globally respected talent acquisition futurist, author, and speaker with over 25 years of experience exploring what’s next in recruiting. Renowned for his expertise in strategic foresight and technology trends, Matt provides a unique perspective that empowers leaders to navigate disruption. His deep industry knowledge and ability to spark meaningful conversations make Recruiting Future a must-listen for talent acquisition and HR professionals everywhere.
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?
Ep 808: The Starting Point For TA Innovation
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.
Ep 805: Hiring's Signal Problem
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.
Producer's note
Steal the structure. Not the show.
Keep the useful structure, then change the audience, point of view, and voice until the idea is unmistakably yours.
