76% Have People Analytics Tools — Why Only 21% Actually Use Them

How AI is Transforming HR: Key Insights and Use Cases

Artificial intelligence is reshaping every stage of the HR value chain, from workforce planning and recruiting to onboarding, performance management, and offboarding. In this episode, we explore where AI delivers the most value — flagging staffing needs early, giving more candidates a fair evaluation, and freeing HR teams from routine admin — while preserving the human judgment that effective people management depends on. A practical guide to adopting AI strategically by starting with low-risk, high-impact use cases.

From 3 Days to 17 Minutes: Medtronic's AI Recruiting Transformation

What if you could cut interview scheduling time by 98%? Medtronic did exactly that — and the results are reshaping what it means to be a recruiter. Medtronic is one of the world's largest medical technology companies: 95,000 employees, 150 countries, 12,000 new hires every year. Before AI, their recruiters were spending two to three business days just to get a single interview on the calendar. Today? It takes about 17 minutes. That's not a pilot number or a projection — it's the measured result of deploying a fully integrated AI recruiting stack across their entire global operation. In this episode, we break down the three tools powering Medtronic's transformation — Paradox's conversational AI agent Sam, HiredScore's talent matching engine, and Workday HCM — and look at what actually changed for the humans in the loop. Because the most interesting part of this story isn't the automation. It's what recruiters are doing with all the time they got back. We also look at what this means for mid-market employers who want Medtronic-style efficiency without Medtronic's enterprise budget — and how tools like OVI are making AI-native recruiting accessible to companies at every scale.

17 Minutes: How Medtronic Crushed Interview Scheduling With AI

What if the thing eating most of your recruiter's day wasn't sourcing or hiring decisions — it was just scheduling? Medtronic found out, fixed it, and the numbers are hard to ignore. In this episode, we break down how one of the world's biggest medical device companies went from 3 days to 17 minutes to schedule a single interview — a 98% reduction — by deploying a stack of AI tools across its global hiring operation. We're talking 95,000 employees, 150 countries, and 12,000 new hires every year. The scale problem was real, and so is the solution. We cover the three platforms powering Medtronic's AI recruiting stack: Paradox's conversational agent 'Sam' for scheduling, HiredScore for AI-powered talent matching, and Workday HCM tying it all together. And we look at what this shift actually means for recruiters — because the story isn't just automation, it's about what happens to human judgment when the busywork disappears. Plus, we look at how mid-market employers can get the same kind of results without Medtronic's enterprise budget. Tools like OVI are bringing AI-native recruiting — automated screening via audio chat, AI sourcing with Sora and Milo — to teams that need to move fast without adding headcount. Plans start at $99 a month. The gap between enterprise and mid-market AI recruiting is closing faster than most HR leaders expect.

85% Claim Skills-Based Hiring. The Research Says Only 0.14% Follow Through.

Eighty-five percent of employers say they've adopted skills-based hiring. But a Harvard and Burning Glass Institute study found that less than 1 in 700 actual hires came from non-degree candidates — even at companies that publicly dropped degree requirements. The aspiration is real. The follow-through isn't. In this episode, we dig into what the 2026 research actually shows about skills-based hiring and AI screening — the quality-of-hire data, the bias findings, and why the EU AI Act's August 2026 deadline changes the calculation for every HR team using automated screening tools. The evidence is clear: when companies genuinely assess skills rather than credentials, hiring quality improves significantly. But Stanford's Institute for Human-Centered AI found that 26% of Black applicants faced discriminatory AI screening in a study of 3.4 million job seekers — a phenomenon they called 'algorithmic monoculture.' The same tool that improves efficiency can amplify bias at scale. We break down what a compliant, defensible skills-based hiring program looks like in 2026: structured rubrics, documented human oversight, and full audit trails. And why the design of your AI screening tool — transparent or opaque — may be the most consequential hiring decision your team makes this year.

76% Have People Analytics Tools — Why Only 21% Actually Use Them

The people analytics market just hit 12 billion dollars, and yet three-quarters of HR teams are essentially leaving their investment sitting on the shelf. In this episode, we unpack why the gap between having a tool and using it effectively is so wide — and how to pick the right platform for where your organisation actually is today. We walk through four distinct market segments: enterprise pure-plays like Visier for large data-mature teams, HRIS-embedded options like Workday People Analytics for those already in that ecosystem, engagement specialists like Culture Amp and Lattice for mid-market culture-first companies, and leaner mid-market standalone tools like Crunchr. Not every org needs a 50,000 dollar a year platform with an eight-month implementation. We also share five practical questions to ask before you book a single vendor demo — starting with the most important one: what is your actual data maturity level right now? The answer changes everything about which platform makes sense. And we close with a tip on where to start if you're just beginning: hiring data. It's structured, high-volume, and immediately actionable — and tools like OVI's Milo screening agent can generate exactly the kind of consistent, auditable data that makes your analytics stack far more powerful down the line.