By 10:47 a.m. on Wednesday morning, billions of dollars had evaporated from wealth management stocks. There had been no earnings miss. No regulatory shock. No fraud. Just a press release from a startup announcing an AI-powered financial planning tool that could analyze tax returns, generate scenarios, and personalize investment strategies in minutes. Within hours, asset managers in London were sliding in sympathy. Brokerage firms in New York were down sharply. Days earlier, legal publishers and data providers had suffered similar fates after the launch of new AI research tools. A wealth manager and a legal publisher have very little in common. Yet, as reported by the FT, their stocks fell for the same reason in the same week.

For the last year, the debate around AI at work has split into two unhelpful extremes. On one side, we have breathless talk of “AI coworkers,” complete with onboarding rituals, performance reviews, and soft-focus imagery of humans and machines collaborating happily at their desks. On the other, we have an anxious counter-reaction that insists this language is dangerous, misleading, and fundamentally wrong, because AI systems are not people and should never be spoken of as if they were. Both camps miss the point. The real question is not whether machines deserve human metaphors, but whether leaders understand what kind of economic force they are unleashing, and what kind of organization that force demands.

For years, Waymo’s autonomous vehicles were known as the politest drivers in San Francisco. They came to full stops, waited patiently at four-way intersections, yielded generously, and behaved with a kind of algorithmic courtesy that seemed almost naive. Then, as the Wall Street Journal recently reported, they began to behave very differently: darting around double-parked trucks, merging aggressively, accelerating the instant a light turned green, even performing the occasional illegal U-turn. Basically, like a NYC taxi driver.

Tokyo moves with the cool precision of an algorithmic machine. Step out of Shinjuku Station at dusk and the city unfurls around you in layers of neon haze—LED kanji flickering like loose packets on a network, billboards pulsing with the heartbeat of a vast digital organism. Crowds slide past in silent, perfect non-collision, as if everyone is running the same invisible protocol. In a metropolis of 37 million, you brace for chaos. Instead you get choreography—an improbable calm humming beneath the circuitry of the streets.

Every technology revolution offers a brief window of unreasonable advantage—an era when the bold can seize opportunities that later become ordinary. This is that moment for AI. The cost of cognition is collapsing. The rules haven’t caught up. The field is open to anyone ambitious enough to rewire their work, their organization, or their industry around machine intelligence. But none of these conditions will hold for long.