People Managing People

AI transformation has a funny way of becoming an organizational X-ray. The companies getting real value from it aren’t necessarily the ones buying the most tools or burning the most tokens. They’re the ones that understand what they’re trying to accomplish, what excellence looks like, and which problems are actually worth solving.
In this episode of People Managing People, David Rice speaks with Zapier’s Chief People and AI Transformation Officer, Brandon Sammut, about why AI ROI starts with organizational clarity, how to build experimentation that survives contact with actual workloads, and why adoption eventually needs to give way to impact. They also explore AI coaching, the growing value of judgment and wisdom, and why the best employers may increasingly be defined by how much more capable people become while working there.
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HR has been told for years to “speak the language of the business,” usually as code for proving it deserves to be in the room. But Dr. Shindale Seale makes a stronger case: this isn’t about self-defense. It’s about leadership. If disengagement, poor management, weak culture, and badly handled transformation all carry measurable financial costs, HR needs to connect the human consequences to the numbers executives use to make decisions.
In this episode, host David Rice and Dr. Seale unpack the “disengagement tax,” why engagement metrics without business impact can become little more than dashboard theater, and what it actually means for HR to become bilingual. They also explore the impossible job organizations have created for managers, why AI tends to amplify the culture it lands in, and whether the CHRO role is big enough for the human side of the transformation ahead.
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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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