Only 10% of senior leaders admit to using AI. Which raises an awkward question: if leadership isn’t really using the tools, who exactly is teaching everyone else how to work with them? Increasingly, the answer is peers. In this conversation from Transform, David Rice sits down with returning guest Kamaria Scott to unpack why AI adoption is becoming less of a top-down transformation initiative and more of a global peer-learning experiment happening in real time.

They explore the growing tension between organizational pressure to adopt AI and the complete lack of capacity many employees have to actually experiment with it. Along the way, they dig into manager enablement, skill atrophy, learning agility, performance management, and the uncomfortable possibility that companies are automating away the very expertise employees need to judge whether AI output is any good in the first place. The result is a candid discussion about why managers may become the bottleneck in AI adoption—and why organizations that failed to build real learning cultures before this moment are now paying for it.

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Most leaders are making AI decisions in the dark—restructuring roles, cutting headcount, and chasing use cases without understanding how work actually gets done. Not the org chart version. The real, messy, task-level reality. And that’s a problem, because when you don’t understand what creates value, automation becomes guesswork dressed up as strategy.

Victoria Pelletier joins the show to challenge the prevailing top-down approach. Instead of starting with AI capabilities, she argues for working backwards from business strategy to task-level workflows, skills, and human contribution. The result? A more grounded, more human, and frankly more effective way to redesign work in an AI-driven world.

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Everything is urgent—until it isn’t. When every ticket is a fire, teams don’t move faster; they burn out. In this episode, Barbara Nicholas (CEO at Polly) borrows a lesson from search and rescue: urgency only matters when it actually changes outcomes. Most white-collar work isn’t life or death, but we’ve built cultures that pretend it is—and people are paying for it in cognitive overload and constant distraction.

Barbara walks through how she operationalizes a triage system across her company—embedding shared language into tools like Slack, Notion, and Jira, and empowering teams to challenge urgency instead of blindly accepting it. From AI experimentation to customer demands and internal comms, this is a conversation about cutting through noise, making better calls under pressure, and remembering what actually matters.

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AI in HR is finally moving out of the pitch deck and into the messy reality of day-to-day operations. In this conversation, Tim Fisher sits down with Josh Rod from HiBob to unpack what’s actually changing—and what’s still just noise. The headline? Most organizations aren’t chasing some agentic, fully automated future. They’re trying to make today’s workflows less painful, faster, and marginally more effective.

But underneath that pragmatic adoption sits a deeper shift: the structure of work itself is being quietly rewritten. When every employee becomes a “manager” of AI, the old hierarchies start to wobble. HR isn’t just implementing tools anymore—it’s being asked to design the operating system for how humans and machines collaborate. And that’s where things get interesting.

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You don’t need to be using AI constantly to be hooked on it—you just need to feel relief when you do. That’s the uncomfortable premise at the heart of this conversation with psychologist and conflict expert Dr. David Zierk. AI doesn’t just give you answers; it removes uncertainty. And in doing so, it quietly rewires how you think, learn, and connect.

What starts as convenience can quickly become dependency. Leaders, in particular, are at risk of trading away the friction that produces insight, the curiosity that fuels growth, and the empathy that sustains relationships. The result? Faster answers, thinner thinking, and a growing gap between knowing what to do and actually doing it.

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AI is supposed to free people up for “higher-value work.” Fine. But what, exactly, is that work? In this episode, David Rice talks with cyberpsychology researcher and psychotherapist Dr. Rachel Wood about the part of AI adoption most organizations keep skimming past: the human cost of automating too much, too quickly, without a real philosophy for what should remain deeply, stubbornly human.

Their conversation cuts through the usual AI optimism and gets to the more uncomfortable truth. Some friction should absolutely go away. Nobody needs to spend an hour copying and pasting spreadsheet data. But some friction is the job: disagreement, discernment, hard conversations, learning by getting things wrong, and figuring out who you are when your expertise is suddenly easier to imitate. This episode is really about that distinction, and why leaders need to stop treating AI as a software rollout and start treating it as a human development challenge.

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Leaders love to frame AI transformation as a technology problem. It’s cleaner that way—tools, roadmaps, implementation plans. But what Anouk Brack lays out here is less flattering and far more consequential: this is a biological stress test, and most leadership teams are quietly failing it.

Under constant uncertainty and pressure, your nervous system defaults to survival mode. That means the very capabilities you’re counting on—strategic thinking, self-reflection, sound judgment—start to degrade. Not dramatically. Subtly. You keep moving, keep deciding, keep “leading.” But you’re doing it with a shrinking field of view and a growing pile of bad bets.

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Your leadership team doesn’t have a strategy problem—it has an execution problem disguised as one. The offsite went great, the vision is crisp, and the slides look expensive. But somewhere between “bold initiative” and “Tuesday morning,” nobody translated strategy into what people should actually do. That gap? That’s where most organizations quietly stall.

Tom Healy argues that L&D is the missing link leaders keep ignoring. Not because it’s ineffective—but because it’s unglamorous. CEOs will talk endlessly about growth, retention, and performance, yet fail to connect those outcomes to how people are trained, onboarded, and supported day-to-day. Meanwhile, AI is making content creation trivial. The real work—the uncomfortable, strategic clarity about culture, behavior, and expectations—is still being skipped.

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When turnover is low, leadership loves to call it stability. Jay Caldwell makes the more uncomfortable point: sometimes it is just fear with better optics. In this conversation, he and David unpack why “quiet staying” can become a serious organizational liability in an AI era—especially when people are still hitting goals, still showing up, and still slowly draining the place of experimentation, risk-taking, and fresh thinking.

They also get into the deeper workforce consequences of AI adoption: why broad rollouts often create anxiety instead of momentum, why the most AI-engaged employees may be the most likely to leave, and why cutting entry-level hiring might solve a short-term budget problem while quietly wrecking your future talent pipeline.

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If your organization looks successful on paper but feels strangely tense in practice, there’s a good chance fear—not excellence—is quietly running the show. In this episode, David Rice talks with Brave Together author Chris Deaver about how fear disguises itself in high-performing workplaces: polished presentations, perfect metrics, and meetings where nobody laughs—and nobody challenges anything either.

Their conversation explores what happens when organizations reward superhero behavior, visibility over collaboration, and certainty over curiosity. The result is brittle excellence and teams that quietly fracture under pressure. The alternative, Deaver argues, is building cultures of co-creation—where leaders shift from being the smartest person in the room to becoming integrators, connectors, and context builders. In a world reshaped by AI and constant disruption, the real advantage isn’t information anymore—it’s shared wisdom, deep empathy, and the courage to build together.

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