People Managing People

There are two ways the AI transformation of work can go. We can hand the keys to the efficiency obsessives and spend the next decade trying to engineer the humanity out of organizations. Or HR can recognize that understanding motivation, organizational design, and how people actually experience work is suddenly a strategic advantage—and start acting like it.
Jessica Zwaan, VP of People Strategy and Operations at Leapsome and author of Built For People and Purpose In Work, joins David Rice to talk about why HR has the raw materials to lead this moment, but also some baggage to lose. They get into purpose washing, why not everyone needs a calling disguised as a job, what AI means for early-career development, and why designing better work requires considerably more than putting a mission statement on the wall and hoping everyone believes it.
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Nobody sets out to build a workforce surveillance system. It usually arrives dressed up as optimization, productivity, wellness, or efficiency. But as AI makes it possible to monitor everything from keystrokes and mouse movements to emotions and physical behavior, the line between legitimate measurement and invasive surveillance gets harder to ignore.
In this episode, I speak with Lynn Parramore, Director of Special Projects at the Institute for New Economic Thinking, about what gets lost when leaders assume everything valuable at work can be measured. We dig into why constant monitoring erodes trust, how algorithms strip context from human behavior, why younger workers have good reason to be skeptical of AI, and why leaders need to get philosophical—not just practical—about where this technology belongs.
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The EU Pay Transparency Directive isn’t just another reporting requirement. As pay reporting expert Tom Heys puts it, it’s closer to the UK gender pay gap regime “on steroids”—combining organization-wide reporting with individual employee rights, restrictions on recruitment practices, and requirements to group jobs of equal value and explain the pay differences within them.
The bigger issue is what happens when organizations are finally required to show their work. Pay transparency exposes weak job architecture, outdated job descriptions, excessive manager discretion, and analytical models nobody can explain. And there’s a broader AI lesson buried in all of this: technology can accelerate analysis, but it can’t absorb accountability. Leaders still have to understand—and defend—the decisions made in their name.
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AI spending continues to hit record highs, yet most organizations are still struggling to translate that investment into better work. In this conversation, David Rice sits down with Ofir Bloch of WalkMe to unpack the findings from the State of Digital Adoption 2026 report and explore why the problem isn't model capability—it's everything surrounding it.
From the massive disconnect between what executives believe employees experience and the reality of day-to-day work, to the growing importance of contextual support and workflow orchestration, this episode argues that the companies seeing results aren't necessarily using the smartest AI. They're removing friction faster than everyone else.
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WalkMe's State of Digital Adoption 2026
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AI is quickly becoming the new test of executive credibility—but there's a growing gap between leaders who use AI and leaders who've fundamentally rebuilt how they work around it. In this episode, David Rice sits down with JC Christian, President of executive search firm Christian & Timbers, to explore why "AI-enabled" is no longer enough and what it actually means to be AI-native at the executive level.
Together, they unpack how executive hiring is changing, why demonstrating real AI deployment experience now matters more than talking strategy, and why adaptability—not decades of experience alone—is becoming the defining leadership capability. As today's competitive advantage rapidly becomes tomorrow's baseline expectation, leaders in every function will need to rethink not just the tools they use, but how they lead.
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