Sam Altman and Dario Amodei are both walking back AI jobs apocalypse predictions as they eye IPOs | FortuneSearchSubscribeHomeLatestFortune 500FinanceTechLeadershipLifestyleRankingsMultimediaTrendingnow1Jeff Bezos wants the bottom half of earners to pay zero income tax—he says nurses making just $75K should save $12K a year2The river that supplies 40 million Americans is down to 23% — and about to make a $25 million bet on one fish3Jamie Dimon said the American Dream was slipping away. JPMorgan just put $40 million on the table to fix it1Jeff Bezos wants the bottom half of earners to pay zero income tax—he says nurses making just $75K should save $12K a year2The river that supplies 40 million Americans is down to 23% — and about to make a $25 million bet on one fish3Jamie Dimon said the American Dream was slipping away. JPMorgan just put $40 million on the table to fix itAIOpenAISam Altman and Dario Amodei are both walking back their AI jobs apocalypse prophecies as they eye blockbuster IPOsBy Sasha RogelbergSasha RogelbergReporterDown Arrow Button IconBy Sasha RogelbergSasha RogelbergReporterDown Arrow Button IconMay 26, 2026, 4:34 PM ETAdd us onOpenAI CEO Sam Altman said he was wrong about his prediction on AI's impact on white-collar jobs.Daniel Heuer/Bloomberg—Getty ImagesTwo of the most influential CEOs in tech spent the last year warning that AI would gut white-collar employment. Now they’re admitting they were wrong, joining other leaders like Goldman Sachs CEO David Solomon in casting doubt on an AI job apocalypse. Recommended Video
OpenAI CEO Sam Altman, in an interview with Commonwealth Bank of Australia CEO Matt Comyn on Tuesday, said he was “pretty wrong” about AI’s economic impact—a reversal from his June 2025 warnings that entry-level roles were at serious risk. Anthropic CEO Dario Amodei, who once claimed AI could eliminate 50% of white-collar jobs, now says automation may actually expand the work people do. Solomon, meanwhile, has argued consistently since at least late 2025 that the panic was overblown—and is now pointing to a century of American economic history to say he was right.
“I’m delighted to ⁠be wrong about this,” Altman told Comyn. “I thought there would have been more impact on entry-level white-collar jobs being eliminated by now than ​has actually happened.”
Altman added that he’s taken a lot of flack for his hype, but better safe than sorry.”People are like, ‘Oh you could have saved the world a lot of fear mongering and a lot of doom and gloom’ but at the time I was like, ‘I see this is a real risk we should probably ​talk about it.’ and it still may.”
Both OpenAI and Anthropic are reportedly preparing to launch their respective IPOs this year, each company with an estimated valuation of $1 trillion.
Two reversals and a vindication
For the OpenAI CEO, his comments walk back his prophecy on AI’s impact on labor. A year ago, Altman told his brother Jack on the Uncapped podcast: “A lot of jobs will go away…we have always been really good at figuring out new things to do…I’m not a believer that that ever runs out.” 
Now he says the displacement he feared simply hasn’t materialized, and a personal experiment reinforced it. He tried delegating his Slack and email responses to AI, then began responding to come again manually.
“We really do care about our interactions with people,” he said. “This thing…is not something that I can imagine myself outsourcing to an AI anytime soon. It really updated me to thinking that the jobs picture is likely to be very different than we thought.”
Amodei’s evolution has been similarly dramatic. While he previously claimed AI could wipe out 50% of white-collar jobs, he reframed automation earlier this month not as a destroyer of jobs but a multiplier of output: “If you automate 90% of the job, then everyone does the 10% of the job,” he said, offering a prediction similar to those made by economists Alex Imas and Tyler Cowen. “And the 10% kind of expands to be 100% of what people do and kind of 10-times their productivity.”
Solomon, meanwhile, didn’t need to change his position because he never held the apocalyptic one. In a recent New York Times op-ed, he offered the same argument he has made since at least late 2025: that American history offers a clear rebuttal to AI job panic, drawing a straight line from the electrification of the 1900s to the digital revolution of the 1990s to today: “The United States has a long track record of creating new jobs in response to disruption … I don’t see any reason to think this dynamic will stop now.”
Despite sectoral shifts, Solomon noted, civilian U.S. employment has grown 145% since 1962. He cited Goldman Sachs research showing data center construction alone has added 200,000 jobs since 2022. A 2018 study by Nobel laureate Daron Acemoglu backs his claim, finding that AI’s displacement effect is typically offset by productivity-driven demand for labor.
“Do any of us feel like we have less to do these days despite the convenience of Excel, email or Zoom?” Solomon said.
What the data shows and what it doesn’t
The data offers a mixed picture. Tech layoffs through May 2026 have passed 115,000, already approaching the 124,000 logged in all of 2025, with Meta, Amazon, and Snap among those citing AI as a driver of cuts. Yet the Yale Budget Lab has found no significant changes in occupational mix or unemployment duration in high-AI-exposure jobs since ChatGPT launched in late 2022.
Tech leaders have been issuing their own predictions on the future of work for years, ranging from AI being able to automate most white-collar work within 18 months, according to Microsoft AI CEO Mustafa Suleyman to Nvidia CEO Jensen Huang’s belief that AI will not have an impact on the number of jobs, but will instead create opportunities for efficiency that will benefit employees leaning into the technology.
Business leaders and economists have started to come to a consensus on why AI could indeed be a boost for labor. In a LinkedIn post in response to Solomon’s op-ed, Box CEO Aaron Levie said he’s betting that Solomon will be proved correct. “If you looked at what work looked like a few decades ago and saw how much faster everything is or easier it is to produce today — even before AI — you’d certainly have been convinced there’d be no jobs left. Yet the opposite has happened. Why?” The answer, he offered, is that automation will not decrease demand for a certain role, but rather increase it, as automation will deliver “the same value proposition, but cheaper.” 
It’s essentially the theory of Jevons paradox that Anthropic’s Amodei and economists like Apollo’s Torsten Slok have also called up in explaining the future of labor. Named for English economist William Stanley Jevons, the paradox refers to the period following the invention of the Watt steam engine, when instead of more efficient coal burning resulting in less coal being burned, the commodity instead became cheaper and more popular. Slok has noted professions like call center employees and radiologists, both with roles vulnerable to automation, have remained steady or increased despite wider AI adoption.
“Lower cost per interaction does not mean fewer interactions,” Slok said in a recent blog post. “It means more customers served, more channels opened and more markets worth reaching. The technology that was supposed to shrink the industry is fueling its expansion.”
In 2001, Fortune first convened the smartest people we know, bringing together CEOs and founders, builders and investors, thinkers and doers. Since then, Fortune Brainstorm Tech has been the place where bold ideas collide. From June 8–10, we will return to Aspen—where it all began—to mark 25 years of Brainstorm. Register now.About the AuthorBy Sasha RogelbergReporterLinkedIn iconTwitter iconSasha Rogelberg is a reporter and former editorial fellow on the news desk at Fortune, covering retail and the intersection of business and popular culture.
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Sam Altman, CEO of OpenAI, and Dario Amodei, CEO of Anthropic, are retracting earlier prophecies regarding the impact of artificial intelligence on job markets, aligning their views with other industry leaders who question the notion of an imminent AI jobs apocalypse. Altman, in an interview, expressed that he was incorrect about the extent of AI's impact on white-collar jobs, noting that the level of displacement feared had not materialized as anticipated. He cited a personal experiment where he delegated responses to AI and then resumed manual work, concluding that the understanding of the jobs picture is likely to be significantly different from previous expectations.

Amodei has similarly evolved his stance, shifting the view of automation from a job destroyer to a job multiplier. He posits that if automation handles ninety percent of a task, the remaining ten percent of the work expands, potentially leading to a ten-fold increase in productivity for those roles. This perspective is supported by economic theory, drawing references to the Jevons paradox, which describes how increased efficiency can lead to greater overall consumption or output rather than simple reduction in demand.

This concept is further elaborated by economists such as Torsten Slok, who notes that lower costs per interaction do not necessarily equate to fewer interactions; instead, they can open more markets and channels for service expansion. This dynamic suggests that the technology intended to shrink an industry is fueling its expansion. Jamie Dimon of JPMorgan, in the context of this discourse, is also contributing to the skepticism surrounding the panic, pointing to a century of American economic history as evidence that the dynamic of creating new jobs in response to disruption persists.

This counter-argument is supported by broader data, which presents a mixed picture. While tech layoffs have occurred, including those citing AI as a driver for cuts, research from the Yale Budget Lab found no significant alterations in the occupational mix or unemployment duration in high-AI-exposure jobs since the launch of ChatGPT in late 2022. Furthermore, the displacement effect of AI in labor is often offset by productivity-driven demand for labor. For instance, the growth in data center construction has added jobs, and a study by Daron Acemoglu supports the claim that AI’s displacement is typically balanced by demand for labor driven by increased productivity. This suggests that automation delivers the same value proposition but at a lower cost, increasing the demand for labor rather than eliminating it. Ultimately, the consensus among some business leaders and economists is that automation increases demand for roles by facilitating greater output, a principle rooted in the historical context of technological revolutions.