Everyone claims they’re “good with AI” on their CV. Almost no one can prove it. As AI tools proliferate across every function, talent leaders face a critical gap: we need people who don’t just use AI, but wield it strategically—and we have no reliable way to identify them. Enter Zapier. The automation platform that helped democratise no-code workflows has developing and refining a practical framework for assessing AI fluency in hiring. Everyone’s been talking about it. But now we’ve got Soeren Winter to unpack it and tell us what it means for Talent Acquisition teams.

• Redefining “AI Fluency” for Hiring
• The Portfolio Approach to Assessment
Distinguishing candidates who’ve memorized one interface from those who understand underlying AI principles and can adapt across platforms, models, and use cases
• Critical Evaluation as Core Competency
• Integration & Workflow Design
• The Ethics & Safety Screen
• Cross-Functional Translation
• Learning Velocity Indicators
• Practical Assessment Design
• Building Internal AI Fluency Benchmarks

AI fluency is now a baseline expectation, not a differentiator—but most hiring processes haven’t caught up. Organizations still screening for “AI experience” on LinkedIn are filling roles with candidates who can’t deliver. Meanwhile, teams using rigorous, practical assessment frameworks are building workforces that genuinely multiply productivity. The cost of getting this wrong isn’t just a bad hire; it’s the opportunity cost of teams waiting months for someone to actually become useful.

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Ep383 is supported by our friends at Greenhouse

AI is reshaping hiring across the UK, Ireland and Germany. But is trust keeping up?

Greenhouse surveyed over 2,200 jobseekers, recruiters and hiring managers to uncover where AI is building confidence in hiring, where it’s eroding it, and what the most trusted employers are doing differently.

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