People Managing People

Most companies say they’re building community. What they often mean is: they launched a Slack channel no one reads, hosted an event with a neon sign and a DJ, watched people post about it on Instagram, and called the whole thing a success. Meanwhile, the people in the room never actually connected.
In this episode, David sits down with Jessie Jacob, Culture First Community Manager at Culture Amp, to unpack why relational atrophy is becoming one of the defining workplace problems of the AI era. Jessie manages a global community of more than 100,000 people, and her argument is simple: if people don’t feel safe, welcomed, or genuinely connected, no amount of “community strategy” will save you. In a world increasingly optimized for efficiency, automation, and performative engagement, human connection is quickly becoming the real competitive advantage.
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AI is speeding up people decisions at exactly the moment those decisions require more care, more context, and frankly, more humility. In this episode, Matt Poepsel from The Predictive Index joins David Rice at Transform to unpack the growing gap between what AI can do and what organizations actually understand about the people data they’re feeding into it. Because while everyone is obsessed with automation, agents, and productivity gains, most managers still don’t know how to ask the most important question: “Do we actually have the right context for this decision?”
The conversation digs into the uncomfortable reality underneath modern workplace AI adoption. Companies are compressing timelines because AI can generate outputs faster, but they’re still operating from old assumptions about productivity, management, and collaboration. The result? Burnout, shallow decision-making, and what Matt calls “work slop” — endless AI-generated summaries, presentations, and outputs that create distance between people while pretending to improve teamwork. The deeper challenge isn’t technological. It’s behavioral. And most organizations still aren’t equipped to deal with that.
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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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Check out this episode’s sponsor: Intuit QuickBooks Payroll
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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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