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

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

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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

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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?

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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?

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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?

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