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

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:

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 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.

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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:

Innovation in recruiting is hard. TA leaders are experts at running their operations, but improving them in a structured way is a different discipline, and the AI revolution has made it one that no one can avoid. Before any function can innovate, though, it has to know where it is starting from, and that is where benchmarking becomes critical.

Recent research from the Recruiting Excellence Foundation, which has assessed the maturity of hundreds of TA teams worldwide, reveals that TA teams are struggling to move from operational to strategic.

So how should TA leaders get started?

My guest this week is Toni de Graaf, Co-Founder of the Recruiting Excellence Foundation. In our conversation, Toni shares what the global benchmark reveals, why so many teams are stuck in operational mode, and how to prioritize the improvements that matter most.

In the interview, we discuss:

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?

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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:

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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:

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