People Managing People

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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AI adoption isn't slowing down—and neither are the risks. The challenge isn't that organizations don't know AI can create problems. It's that employees are already using it in ways leaders can't fully anticipate, while governance models built for yesterday's technology struggle to keep pace.
In this episode, David Rice sits down with AI ethics expert and The Ethical Nightmare Challenge author Reid Blackman to explore why traditional AI governance is falling behind the rise of generative and agentic AI. Rather than treating ethics as a bureaucratic exercise or a brake on innovation, Reid argues that the organizations moving fastest are the ones that learn how to identify potential "nightmares" before they become public failures. The conversation offers a practical framework leaders can begin using immediately—without waiting for enterprise-wide policies or perfect alignment.
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AI isn't creating high-performing teams—it’s exposing the difference between teams that already know how to work well together and those that don’t. In this episode, David Rice sits down with social psychologist and Superteams author Ron Friedman to unpack new research on what separates the top 8% of teams from everyone else. The conversation challenges the assumption that AI is a universal productivity boost, revealing instead how it can amplify poor habits, deepen burnout, and create false confidence when used without judgment.
They also explore why the best teams protect focus over busyness, replace brainstorming with brainwriting, rethink meetings entirely, and create cultures where experimentation—not perfection—drives performance. If you're leading people through the AI era, this episode offers a practical blueprint for building stronger teams instead of simply working faster.
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AI transformation doesn't fail because the technology isn't good enough. It fails because organizations try to layer it on top of cultures that were already struggling with trust, learning, experimentation, and leadership. In this conversation, David Rice sits down with Meagan Bond, Founder and CEO of The Human Method, to unpack why psychological readiness—not technical readiness—is the real foundation of successful AI adoption.
Together they explore the hidden costs of dysfunctional culture, why managers play an outsized role in determining whether AI succeeds or fuels burnout, and why organizations chasing quick AI wins often undermine their long-term competitive advantage. If culture is treated as an afterthought instead of infrastructure, AI simply accelerates the problems that were already there.
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