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.

At first glance, Disney’s recent moves look contradictory. The company announces a sweeping partnership with OpenAI that allows its characters to appear inside generative tools like Sora, while almost simultaneously firing off cease-and-desist letters to Google and pressing forward with aggressive litigation against Midjourney. To some observers, this looks like confusion. To anyone who has watched Disney for long enough, it looks like something else entirely. This is a company that has spent a century mastering the art of adapting control to new forms of participation.

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.

In 2013, a quiet software developer known to his colleagues as "Bob" became briefly infamous when investigators discovered that he had secretly outsourced his entire job to a contractor in China. He had mailed his security credentials overseas, paid the contractor a fraction of his six-figure salary, and spent his own workdays browsing Reddit and watching cat videos. Yet his performance reviews were stellar. Bob was, by every visible metric, one of the company’s best engineers. When his secret arrangement was uncovered, he was fired. But a decade later, his story looks less like a strange aberration and more like a preview of work in the age of AI.