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:

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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:

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

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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:

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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:

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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:

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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:

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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

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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

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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?