The move may offer an early glimpse of how AI is actually reshaping the labor force: not by immediately displacing the tactile, mundane factory roles everyone expected, but by hollowing out the white-collar ranks that run them.

Amazon announced Tuesday that it will cut roughly 14,000 corporate jobs, or about 4% of its white-collar workforce, as part of a restructuring meant to “reduce bureaucracy” and “remove organizational layers,” according to a memo. In the memo, Beth Galetti, senior vice president of people experience at Amazon, said the cuts are designed to make the company leaner and more agile as it expands its investments in generative AI. In plain terms, it’s a bet that algorithms can handle many of the coordination, reporting, and decision-making functions once reserved for human managers.

Over the past year, CEO Andy Jassy has been frank about Amazon’s transformation.

 “We’ll need fewer people doing some of the jobs that are being done today,” he told employees earlier this year, citing generative AI’s growing role in planning, analytics, and forecasting. Those tools, he said, are already helping teams “move faster and make better decisions.”

That logic is spreading across corporate America. Generative AI systems have become adept at precisely the kinds of tasks that fill middle managers’ days: synthesizing updates, drafting memos, producing status reports, and summarizing meetings. 

It’s unclear if the layoffs announced Tuesday are a direct result of that calculation, that gen AI can perform middle-management tasks just as well, or better, than humans can. However, for executives under pressure to boost productivity at lower costs—and especially for those with a penchant for cutting—the appeal of flattening the hierarchy is obvious. 

Yet there’s an irony here. Amazon—the company that pioneered warehouse automation and made robots the poster child of blue-collar disruption—is now signaling that the white-collar workforce may be first to feel AI’s bite. Analysts at Gartner estimate that by 2026, one in five organizations will use AI to eliminate at least half of their management layers.

The timing couldn’t be worse for workers, particularly younger ones, who are trying to move up. Federal Reserve Chair Jerome Powell warned in September that hiring has slowed “in a noticeable way,” especially for early-career employees. Powell and other economists have acknowledged that the economy has entered a “low-hire, low-fire” phase, where companies are reluctant to add jobs even as growth continues. 

“If people are getting more productive, you don’t need to hire more people,” Airbnb CEO Brian Chesky told the Wall Street Journal. “I see a lot of companies preemptively holding the line, forecasting, and hoping that they can have smaller workforces.”

Amazon isn’t alone. This week, Target announced its first major round of layoffs in a decade, cutting just shy of 2,000 jobs. Paramount, fresh from its merger with Skydance, is also laying off 1,000 jobs this week as it undergoes restructuring. 

If AI flattens corporate hierarchies, creating a “low-hire, high-fire” market, that could further erode the traditional career ladder and potentially be destructive across all layers of the economy. This just so happens to be the picture painted by the latest Challenger, Gray & Christmas report, released Oct. 2. According to the outplacement and executive coaching firm, U.S. employers announced 946,000 job cuts so far this year, the highest year-to-date total since 2020, with over 17,000 explicitly attributed to artificial intelligence and another 20,000 tied to automation and “technological updates.” Tech firms alone have shed 108,000 jobs in 2025, and retail layoffs are up 203% year over year as companies brace for a slower holiday season, the firm said.  “It’s very likely job cut plans are going to surpass a million for the first time since 2020,” Andy Challenger, senior VP at Challenger, Gray & Christmas, wrote in the report. “Previous periods with this many job cuts occurred either during recessions or, as was the case in 2005 and 2006, during the first wave of automations that cost jobs in manufacturing and technology.”