The Inertia Problem: Why FOBO Is Rational in the Age of AI

“The people in the organization who can lead that change management are the ones who are going to create an amazing career opportunity for themselves. But it’s hard to do, and that’s going to slow down the rate of change, just the amount of inertia in the economy.” — Chamath Palihapitiya, All-In Podcast, February 27, 2026

When a venture capitalist worth billions validates what change practitioners have been saying for years, you pay attention. Chamath didn’t just acknowledge that AI is transforming the workforce; he named the thing that keeps transformation practitioners up at night: inertia. Not a lack of technology. Not budget. Inertia. The deeply human resistance to change that no software release can solve.

And here’s what struck me: he said this in the same breath as talking about AI accelerating the rate of change. We are living inside a paradox! The faster the technology moves, the harder it becomes for people and organizations to keep up. That gap is where the real work happens. That gap is where I work.

There’s a name for what people are feeling. Its called FOBO — Fear of Becoming Obsolete.

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The Old Deal Is Cracking

For most of my career, there’s been this implicit promise that engaging with new technology was clear: learn it early, get ahead. The people who figured out enterprise software, cloud platforms, and blockchain earned more and became indispensable. Technology adoption was a career accelerator.

That social contract is cracking.

And I want to be careful here — most leaders are not indifferent to their people. Many of them are caught between a financial mandate handed down from the top and the human realities of their teams. Cost pressure is real, and the pressure to demonstrate AI-driven efficiency gains is intense. But in the rush to hit a number, the message that is heard is: learn this tool so we can right-size your role. 

If that’s the signal employees are receiving, then Fear of Becoming Obsolete (FOBO) isn’t a mindset problem. It’s a rational response to what organizations are communicating.

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FOBO is logical until you change the signal.

I practice organizational change management through the lens of Prosci’s ADKAR model: Awareness, Desire, Knowledge, Ability, Reinforcement. In my experience, Desire is the most misunderstood step. 

Organizations pour time and energy into Awareness through all-hands meetings, leadership cascades, and training mandates. But you cannot manufacture Desire through a memo. Desire comes from belief. Specifically, the belief that change will benefit me.

Right now, employees don’t have that belief. And until organizations change what they’re signaling, no amount of AI literacy training will close the adoption gap. People are watching what happened to call center workers, junior coders, testers, and entry-level analysts, and they’re doing the math.

We know from history that the internet eliminated travel agents but created UX designers and growth hackers. Roles no one could have named in 1995. AI will undoubtedly create second and third-order industries we can’t yet see. The challenge is that the cycle is faster this time and the lag between job displacement and job creation feels more existential when you’re inside it.

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Build the Thing 

Recently, on the same All-In podcast, Jason Calacanis mentioned that 15 people in his company were trained and required to build their own AI agent. Not use one. Build one.

That detail is the most practical piece of change management advice I’ve heard in this AI cycle. When you build something, even something small, you move from passive consumer to active creator. You develop Knowledge and Ability simultaneously, and in doing so, you often discover that the thing you feared is actually a tool you can shape. That shift from “AI is happening to me” to “I am making AI work for me” is where FOBO begins to dissolve.

Organizations serious about reducing workforce inertia should consider this approach. Don’t just train people to prompt an AI. Have them build something, a workflow, an agent, an automation; one that solves a real problem in their day. The learning is secondary to the feeling of authorship.

Chamath is right that change management will define who thrives in this moment. Real change management has always been about people first. In the age of AI, that truth hasn’t changed. It starts with giving people a reason to believe the future includes them.

Let’s figure it out together. 💚

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_{Source: Chamath Palihapitiya, All-In Podcast — “Software Stocks Implode, Claude’s Hit List, State of the Union Reactions, Trump’s Tariff Pivot,” February 27, 2026. Listen here.}