From tool overload to real outcomes

There’s no shortage of innovation in hiring right now – new AI tools, new features and new promises every week. But for most teams, more tools haven’t led to better outcomes. They’ve made it harder to know what’s actually worth using. That’s the reality behind this edition: more tools, more problems – unless you know how to pick and to use them well.

That’s exactly why we’re bringing Open for Ops to New York and San Francisco in June. It’s a hands-on event for TA Ops leaders designed to help you step back from the noise, learn from what’s working in real teams and walk away with practical ways to simplify your hiring systems. You’ll get clear frameworks to prioritize AI investments, reduce complexity and build processes that hold up under pressure.

One session we’re especially excited about is AI that actually works: real experiments, real trade-offs. This session breaks down how teams have tested AI across sourcing, screening, scheduling, interview intelligence, fraud and reporting – what delivered impact, what didn’t and how they decided what to scale or cut.

The takeaway is simple: map your funnel, identify where decisions break down and apply AI in a few high-impact moments where it can improve signal or reduce effort.

The Recruiter’s Desk: More AI, more decisions – here’s how to make them better

AI is showing up in more parts of the hiring process – and now, AI interviews have joined the mix. But has it really made hiring easier? According to new Greenhouse data, 63% of candidates have already experienced an AI interview, yet most say they weren’t clearly told AI would be involved. That gap points to a broader issue: teams are layering in AI without rethinking how hiring works end to end – from how candidates experience the process to how teams evaluate, align and move people forward.

So what changes now that AI is here? We brought together insights from experts featured in The Recruiting Roadshow to highlight what’s working in practice:

Make AI part of a defined process: When structure isn’t clear, outcomes start to vary. As Jessica Gousse explains, hiring still needs to “flow with the way a human works,” so AI should support a consistent process – not sit outside of it.

Set clear evaluation criteria upfront: Alignment breaks down when teams don’t agree on what they’re assessing – skills, competencies or signals of success. Jeremy Lyons captures the mindset: “Just because we can doesn’t mean we should.” Define what matters first, then apply AI deliberately.

Use AI to support the system, not compensate for it: As Brandon Jeffs puts it, “Teams aren’t breaking because they’re not working hard enough – it’s because the systems aren’t supporting them.” AI should strengthen those systems, not add more layers to manage.

Thank you

Thank you for reading this edition of Modern Recruiter! We’ll see you next time for more must-reads, events and open jobs to keep you updated on the latest news and insights in the industry.

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