Attracting Tech Talent in the Age of AI: Keeping Hiring Human, with Katie Cormier, Head of People at EdgeTier
Katie Cormier is Head of People at EdgeTier, an Irish AI-native business that provides data and insights to the customer support sector. Katie has an unusual path into the role: she spent years in recruitment, ran her own agency for a couple of years, then moved back in-house. As EdgeTier’s first People hire, she scaled the team through its Series A push, hiring around 60 people in her first 18 months, largely working solo before bringing on a coordinator six months in.
In this episode you’ll learn:
✅ Why EdgeTier deliberately tests for ambiguity tolerance, and why the “right skill set” from a big tech background often means the wrong cultural fit for a fast-moving start-up
✅ Why Katie doesn’t rely on psychometric testing, and uses structured, behavior-based interview questions instead
✅ How EdgeTier’s ATS (Ashby) flags fraud signals and AI-generated application answers, and the tells that give an AI-written response away
✅ Where AI actually adds value in recruitment: surfacing past candidates who reached final stage months ago, scheduling automation, and AI note-taking in interviews
✅ The rule Katie won’t compromise on: every final-stage candidate gets a phone call and real feedback, not a generic email
✅ Why speed, not perks, is what wins the best candidates in a market where every offer has a competing offer on the table
The takeaway
Katie’s experience cuts through a lot of the noise around AI in hiring. Her team uses AI precisely where it saves time on repetitive tasks, flagging fraud, resurfacing past applicants, taking interview notes, without ever letting it replace the human moments that actually matter: real conversations, real feedback, and real judgment about who will thrive in a specific culture. Her rule that every final-stage candidate gets a phone call, win or lose, is a simple standard most companies still fall short of.
This episode is for HR leaders, talent acquisition teams and founders scaling a start-up who want a practical, unsentimental view of where AI belongs in hiring, and where it doesn’t.
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