Recruiting Future with Matt Alder - What's Next For Talent Acquisition, HR & Hiring?

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?

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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?

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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?

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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?

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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.

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