People Managing People

Most companies are still figuring out what an AI agent should actually do. JLL has moved well past that question. With agents operating across facilities management, brand communications, and corporate functions, the company is learning that the hardest problems aren’t necessarily technical—they’re about proving value, building trust, and making sure AI solves an actual business problem instead of becoming another expensive corporate science project.
Recorded at the AI4 conference in Las Vegas—with some of the inevitable conference-floor background noise—this conversation between host David Rice and Carlin Power, Global VP of AI and Platform Technology Enablement at JLL, explores what it actually takes to deploy AI at scale. They discuss why ROI needs to live inside the P&L, how decentralized AI development can accelerate useful innovation, and why eliminating entry-level roles in the name of efficiency may be exactly the wrong lesson to take from AI.
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Recorded live at the AI4 conference in Las Vegas, this conversation puts David Rice and Dr. Lilian Ajayi Ore—AI lead faculty and lecturer in strategic communication at Columbia University and co-author of The Power of the Learning Mindset—in the middle of one of the biggest questions surrounding workplace AI: Are companies gaining efficiency while quietly weakening their people’s ability to think? With the energy of a live conference comes some background noise, but the discussion cuts through it.
David and Dr. Ore explore cognitive debt, skill decay, and why the usual AI metrics—seats, logins, prompts, adoption rates—say very little about whether workforce capability is actually improving. They discuss the risks of outsourcing judgment and critical thinking, the loss of institutional knowledge when organizations replace people rather than reskill them, and why AI transformation needs to be treated as a talent priority alongside a technology priority. Because faster work isn’t much of a win if the people doing it are slowly losing the skills that made them valuable in the first place.
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AI may be changing the work, but the bigger risk is what happens when organizations optimize so aggressively for today’s efficiency that they stop building tomorrow’s capability.
Recorded live at the AI4 conference in Las Vegas, host David Rice sits down with Dr. Jana Brown, Chief Human Resources Officer at eHealth, to unpack the long-term consequences of shrinking entry-level pipelines, why HR needs “transformation fluency” rather than technical expertise alone, and what separates useful AI initiatives from expensive corporate hobbies. They also explore the human and operating systems that have to move together if transformation is going to stick—and why the technology itself is rarely the thing that sinks an AI project. Listeners may hear a little more conference-floor noise than usual, but that’s the price of capturing these conversations where they’re actually happening.
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AI in HR has a credibility problem: the technology is getting better at spotting patterns, summarizing data, and automating work, but none of that guarantees a better employee experience. In this conversation, Motivosity Chief Product Officer Jesse Dowdle and VP of Engineering Dano Gillette make the case for “appreciation intelligence”—using AI to remove administrative friction without automating the human moments that actually make recognition meaningful.
The bigger opportunity isn’t an AI-generated thank-you note. It’s giving HR and frontline managers a richer picture of employees, surfacing signals before problems become crises, and turning data into useful action. But there’s an important line running through the conversation: AI can recommend, filter, moderate, and nudge. Humans still need to own the judgment.
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When people stay quiet at work, organizations lose more than participation. They lose ideas, warnings, customer insight, process improvements, and market intelligence that never make it into the room. Seema Bhansali calls this the silence tax—the hidden cost companies pay when their environments make self-censorship the safer option.
In this episode, Seema joins David Rice to unpack why “speak up” advice misses the real problem. Employee voice isn’t simply a confidence issue; it’s shaped by systems, social risk, management behavior, and the environments leaders create. They also explore why this matters even more as companies adopt AI, and why communication needs to be treated less like a soft skill and more like an operational capability tied to performance.
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