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AIPROPX ReportFortune · 2h ago
Why the AI economy is like a bad dating app — drowning in decks, pilot purgatory — and it’s playing out like the dotcom bubble,…
Amy Webb was on her long Sunday bike ride, the one she takes when she’s not training for a race, when the thought arrived fully formed. As she posted on LinkedIn recently: every CEO she talks to is buying abundance, and none are budgeting for the cost of abundance. And she talks to CEOs every day for a living.
Webb, 51, runs the Future Today Strategy Group, the foresight and consulting firm she founded in 2006 after a career in data journalism that led to her subsequent interest in machine learning. Webb, who also teaches at NYU’s Stern School of Business, published The Big Nine , which named nine American and Chinese tech giants as forces that would dominate in a world marked by artificial intelligence and a full-scale tech cold war, so she’s used to being ahead of her time, and she’s used to being frustrated by the world being behind the schedule she sees in her head.
So when Webb told Fortune that she sees something like a bust coming for corporate AI spending, it’s worth pausing on the precise dynamic she’s describing. “AI is making production cheap,” she said, “but it’s making everything else in companies much more expensive.” The corporate world, she added, is going through something like what millennials and Gen Zers experienced as dating-app fatigue.
“The best thing [for a dating app] is to never get married,” Webb said, adding that she sees the same thing playing out in the endless series of generative AI pilots. She said executives tell her they’re in “pilot purgatory”: dealing with unending pilots and “enormous productivity but [they’re] not sure what to do with that.”
Venture capitalist Marc Andreessen , meanwhile, said in March that large companies are overstaffed by as much as 75% and were using AI as a “silver bullet excuse” for cuts that reflect pandemic-era overhiring. A separate analysis by Oxford Economics found AI-cited layoffs accounted for a mere 4.5% of total U.S. job losses despite outsized headlines.
‘It feels like you’re buying abundance’
Webb, who speaks with between 100 and 150 CEOs a year, said she’s most focused on a bubble that sits apart from what’s happening on Wall Street: the strange way that AI is deforming work without actually changing it much at all.
“It feels like you’re getting a lot when you invest in AI,” Webb said, “it feels like you’re buying abundance. But that abundance ends up costing much more down the road.” It’s not a question of long-term investment versus short-term gains, an old business trade-off. “This is immediate satisfaction, followed by: can I productize this? Can I put it in a workflow?” AI is making companies feel like they’re winning, a sensation of “I’m getting away with it,” and that’s driving a lot of enthusiasm and adoption.
At the same time, she said she can count on one hand the number of companies that have figured out a sustainable way to pull off this kind of experimentation. One of her clients had run 14 or 15 generative AI/agent pilots since the start of the year and used Amazon’s famous two-pizza rule, in which no team was big enough that it would take more than two pizzas to feed them. None of them scaled. “They’ve gone through a lot of pizza.” Part of the issue is that pilots often run without integration into legal and IT, and so executives don’t embed the pilots into their infrastructure, but restart from zero each time. “That costs a lot of money,” she said.
The pattern shows up in the data: A Bain & Company survey of 951 global companies published in June found that nearly 40% of companies that measured their AI cost savings landed below 10%, despite having targeted returns of 11% to 20%. But to Webb’s point, the shortfall hadn’t slowed spending, as 90% of companies surveyed said they’re increasing their AI budget anyway.
Drowning in decks
Outside of pilot purgatory, there’s the drowning-in-decks issue. Webb recalled an executive who recently shared that their direct reports were experiencing something like decision paralysis, not because they had too little information, but because they were being buried in too much analysis to process. Another described the problem to Webb as “insta-decks”: presentations that used to take a week to build now take a day, but the same team is receiving five times as many of them. It doesn’t help, she added, that “Claude has a little bit of a verbosity problem,” producing 10 pages when you only need one.
“The more a company uses these tools,” Webb added, “the more generic ideas are spit out.” This isn’t the same thing as AI slop, she said — it’s something different. “It’s fine with me if something was not written necessarily by a person, if the rest of the information is useful.”
Webb said she asks nearly every CEO she meets: if AI freed up 10% of your total capacity tomorrow, where would you deploy it? “So far, I haven’t gotten an answer.” Of all the time being saved, she said, nobody seems to have the job of harvesting all these productivity gains. “I’d bet at most companies, people are prioritizing speed over creating new ways of thinking. And then you’re not learning anything.”
Psychologists have begun studying the phenomenon of “cognitive offloading”—delegating mental work to a tool rather than doing it yourself—and recent research finds that when AI takes over core reasoning tasks, people’s sense of ownership over the resulting work declines. It’s “automating something that people very much feel they have ownership over,” Webb said, adding that you can see this in debates in Hollywood...
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