Businesses are pouring millions into generative AI—chatbots, copilots, “agents”—while quietly ignoring the other half of the AI stack that’s been delivering measurable value for decades. Predictive AI doesn’t write poetry. It predicts who’s going to churn, which transaction is fraud, and which customer is worth contacting. It calculates probabilities and helps you act on them at scale. Not glamorous. Just effective.

In this conversation, Eric Siegel—author of The AI Playbook and founder of Machine Learning Week—makes a subversive claim: most organizations should be investing at least as much in predictive AI as generative AI. The problem isn’t the math. It’s the gap between tech and business. Companies celebrate models as value. But the model isn’t the value. Acting on predictions is.

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You were told AI would clear your calendar. Instead, you’re answering 800 chats a day and wondering what, exactly, you accomplished. Productivity is up. So is the volume. You 10x your output and somehow inherit 10x the work. Welcome to the hamster wheel.

In this episode, Eliza Jackson, COO at ButcherBox, and I unpack the real transformation behind AI at work. It’s not about learning a new tool. It’s about unlearning how you work. It’s about rethinking what you own versus what you delegate. And it’s about building the kind of resilience and mindset that don’t show up on a résumé—but determine whether your team can survive what’s coming.

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Most employees are using about 1% of what AI can actually do. Not because they’re lazy. Not because they lack access. But because no one has shown them how to think with it. Meanwhile, somewhere in Silicon Valley, a 23-year-old is running a startup like they’ve got 28 PhDs sitting beside them—for a penny a minute. That gap isn’t theoretical. It’s operational. And it’s widening by the hour.

In this conversation, Kevin Surace and I dig into what that gap really means—for your productivity, your profession, and your relevance. From three-paragraph prompts to million-dollar consulting projects replicated in minutes, we explore why this wave looks familiar (desktop computers, the internet, Excel) and why it’s moving faster than all of them. Resistance isn’t noble. It’s career-limiting.

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So yeah—your dashboards look great. Your team’s shipping faster, summarizing more, “getting leverage” with AI… and all the while you might be quietly trading away the one asset you can’t buy back on a subscription plan: human judgment.

In this episode, I’m joined by Dr. Vivienne Ming—neuroscientist, entrepreneur, and an “AI realist” who has zero patience for utopian hype or Skynet fan fiction. Vivienne lays out a clean fork in the road: cognitive automation (AI does the thinking for you) vs. cognitive augmentation (AI makes you think better—often by making the work harder). If your AI strategy is mostly about convenience, this is your gentle-ish warning that convenience is not a strategy. It’s a sedative.

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AI didn’t replace your job—it replaced your value proposition. In this episode, we sit down with Taylor Blake, SVP of AI Labs at Degreed, to talk about the uncomfortable truth facing L&D teams: if your job is framed as delivering content, unblocking employees, or feeding answers in the flow of work, AI is already doing it better, faster, and without your calendar invite.

But where AI stops short is precisely where L&D’s future begins. Taylor shares how her team at Degreed lives as “customer zero,” using their own tools before shipping them to clients—which means they’re embedded in the mess, not just pitching the promise. From readiness over responsiveness to the emotional toll of relentless efficiency, this conversation explores what it really means to build capability in a world where one employee now has the power—and pressure—of ten.

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Most business leaders are still talking about AI as if it’s just another “productivity upgrade.” Meanwhile, the world building the future — massive data centers, AGI R&D, and winner‑take‑all investment — is sprinting ahead without guardrails, ethics, or broad societal input. In this conversation, researcher Christopher DiCarlo pushes executives to confront a reality most aren’t prepared for: AI isn’t a tool you add to the org chart, it’s a paradigm shift that will redefine work, power, human purpose, and morality.

This episode is part wake‑up call, part philosophical intervention. It challenges HR leaders and executives to stop asking “how much more productive do we need to be?” and start asking “what kind of future are we building — and at what cost?” If you’re still waiting for a miracle app to solve everything, this conversation will shift your perspective on AI strategy, ethics, and leadership responsibility.

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AI is everywhere—and yet, in most organizations, it’s nowhere. People are intrigued, but unsure. Leaders evangelize, but workflows stay the same. Curiosity, it turns out, is not a strategy. In this episode, we’re joined by Justin Angsuwat, Chief People Officer at Culture Amp, to unpack how they flipped the script. In just six weeks, they moved nearly 80% of their workforce from passively curious to actively confident in using AI—without top-down mandates or perfectionist paralysis.

We get into the nuts and bolts of the “Accelerate” program, the value of separating exploration from expectation, and why confidence—not usage metrics—is the better north star for early-stage AI adoption. Justin also shares the uncomfortable truths about integrating AI into daily work, especially for senior employees whose identities are tied to outdated workflows. If your team is hovering in AI limbo, this conversation is your blueprint for action.

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For the past 18–24 months, HR teams have been asked a blunt question: What are you doing with AI? The response has often been activity without strategy — policies, guardrails, governance frameworks — busy work that signals compliance rather than creates value. Dr. Dieter Veldsman joins David to diagnose this pattern of urgency → paralysis → compliance, explain why it’s holding HR back, and show how a deeper sense‑making process is the real lever for progress.

Dieter argues — and the data backs it up — that most HR orgs focused on what can’t be done with AI, not what should be done to drive business value. The root isn’t technology ignorance, it’s cultural: HR has treated AI like a tech project when it’s fundamentally a people and organizational transformation. This episode walks through how to break the compliance trap, structure experimentation with purpose, and expand the CHRO role into the architect of the human‑machine ecosystem.

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If you’ve noticed that effort stopped being a differentiator, this episode will explain exactly what shifted — and what actually drives value in modern work. Lena Thompson, a leadership consultant with a systems analysis background, argues that the era where hustle and logic alone produced breakthroughs is over. AI can outpace us on sheer processing — but it cannot manage emotional energy, and that’s where the real work of leadership now lives.

We dig into what emotional energy actually is (it’s not soft feel‑good fluff — it literally shapes brain function), why unprocessed emotions create cognitive blockages, how leaders can regulate emotional energy to improve decisions under pressure, and practical tools you can use today. This is an episode about leading from within, not just doing more — because the quality of your energy determines the quality of your impact.

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If your organization still views HR as the compliance cops standing by to squash complaints about an AI mandate, this episode is going to upend that thinking. David sits down with Tim Fisher—Head of AI at Black & White Zebra and longtime observer of organizational behavior—to dissect the real challenge of AI adoption in business. What he’s learned from being an “HR outsider” is simple but staggering: most companies are treating AI like a tech rollout when the real work is massive human change at scale—the kind of transformation HR has always lived in, even if others failed to notice.

From the cavernous disconnect between what HR is being asked to do with AI and what they’re actually equipped to do, to why HR leaders must be at the table before strategy is set (not as cleanup crew), today’s conversation strips away the myth of AI as just another productivity tool. Tim and David map the human, technical, and leadership gaps that are shaping every AI effort today—and why success in 2026 will look nothing like a rushed compliance sprint.

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