There are two phrases that have reliably marked every great financial bubble in modern history.
The first is “this time is different” — what Sir John Templeton called “among the four most costly words in the annals of investing,” the signal that investors have begun rationalizing sky-high valuations by convincing themselves that old metrics no longer apply. Carmen Reinhart and Kenneth Rogoff gave the phrase its academic weight in their landmark 2009 book This Time Is Different: Eight Centuries of Financial Folly, documenting how governments and investors had repeatedly convinced themselves that past crises wouldn’t recur — and were always proven wrong.
The second phrase is less discussed but equally diagnostic: “nobody knows anything.” It is what you say when the honest position is uncertainty so complete it borders on paralysis.
In May 2026, both phrases are everywhere. And remarkably, they are often coming from the same mouths.
“Nobody knows anything,” said Ethan Mollick, the Wharton professor and one of the most closely followed voices on AI in the world, speaking to several hundred corporate leaders at the New York Public Library on Thursday morning. “I spend my time talking to AI labs, famous people, I talk to CEOs all the time, and nobody knows anything. We’re all making this up as we go along. So anyone who’s like, ‘We have the playbook’ — they’re lying to you.”
The Number Behind the Noise
Start with the number that puts all of it in perspective: 0.1%.
That is Bank of America’s own estimate for how much AI is currently lifting economy-wide productivity per year — published in the same report that called AI bigger than electricity and the internet combined.
Similarly, Goldman Sachs found “no meaningful relationship between AI and productivity at the economy-wide level” in March, while simultaneously reporting a median 30% productivity boost in the two sectors, customer support and software, where AI has concentrated most.
The arithmetic behind the 0.1% is straightforward. AI can currently transform about 20% of all workplace tasks. Only 23% of those tasks are cost-effective to automate at today’s prices. Automated tasks save roughly 27% in labor costs. Labor is about half of all costs. Multiply it out and the theoretical ceiling today is a 0.66% gain in labor productivity — before friction, slowness, and institutional inertia compress the realized number further.
This is BofA’s own math, used to build its own bull case. Every serious argument about AI’s economic future — bull and bear alike — is an argument about whether, how fast, and at whose expense that gap closes. What follows are the two strongest versions of each side.
The man who killed the playbook
Mollick’s “nobody knows anything” means, in a sense, that the tech industry is in its Hollywood phase. The same expression was a famous aphorism from William Goldman, widely considered one of if not the greatest screenwriters of all time, when he sat down to write his memoir, Adventures in the Screen Trade, in 1983:
“Nobody knows anything,” concluded the man behind Butch Cassidy and the Sundance Kid, All the President’s Men, The Princess Bride and many more, picking up two Oscars along the way. “Not one person in the entire motion picture field knows for a certainty what’s going to work. Every time out it’s a guess — and, if you’re lucky, an educated one.”
Mollick sounded downright Goldmanish as he addressed the New York Public Library crowd. “There’s no playbook,” he said. “We’re figuring it out. On one hand, that’s terrifying. On the other, it’s great — because that means if you create your own playbook, there’s actually a source of advantage for you in that.” Tell that to the Hollywood studios that couldn’t stop putting out bombs.
The box office bomb has its parallel in the stock-market crash, and Mollick said the fates come down to two simple but difficult questions. “The biggest picture, there’s only two questions that actually matter a lot, which is how good and how fast? How long does this exponential curve continue and at what point does it ease off and how sharp will it be? That determines everything else.”
All the talk today is based on an understanding of where things are today and assuming that the future resembles the past, he added, and the “jagged frontier” of AI advancement, a phrase Mollick popularized, makes that truly unstable. But of course, both Templeton and Mollick can’t be right. The playbook has to still matter, or it truly is different this time.
The specific mechanism he identifies for why the curve’s economic payoff is taking so long to arrive is organizational rather than technological — and it is more precise than anything in the bank reports. Mollick cited a piece he wrote in the Economist, about how the IT department is “where AI goes to die” — not because IT is malicious, but because risk-reduction mandates are structurally hostile to experimentation.
“KPIs are the biggest enemy at this point. They force you into very bad paths in the experimentation phase,” he said. “The very nature of saying we need a 10% improvement constrains the kind of use cases that you see.”
Breakthrough applications of AI — the ones that don’t improve existing processes but replace them entirely — cannot be KPI’d into existence. This is the organizational manifestation of the 0.1% problem: not irrational exuberance but rational conservatism, embedded in every quarterly earnings call and performance review cycle.
The sharpest evidence that nobody knows anything — sharper even than the 0.1% figure — comes from Mollick’s observation about the AI companies themselves. “It’s weird that the AI companies are all now building their own consulting arms to do AI deployment. If the models are so good that you think they’re going to destroy all white-collar jobs, shouldn’t they also be able to help you deploy systems?”
The companies that built the technology and are most bullish about its capabilities cannot use that technology to answer the most basic practical question: how do you actually deploy it?
Depending on how you look at it, it’s evidence that there is no playbook for what’s happening now, or it’s the oldest playbook in the world: there’s a new player in town, and it has something everyone else needs.
