Something strange has been happening in corporate America. Company after company announces layoffs, and the press release almost always includes the same line: "We're investing in AI." But if you look closer, the story often falls apart. Many of these cuts have less to do with artificial intelligence and more to do with a hiring spree that went too far during the pandemic.

The pandemic hiring bubble

Between 2020 and 2022, tech companies experienced explosive growth. Remote work, e-commerce, cloud computing, and digital entertainment all surged as the world locked down. Companies responded by hiring aggressively, assuming the demand would last.

It didn't. As the pandemic wound down, demand normalized. Suddenly, companies like Google, Amazon, Meta, and Microsoft found themselves with tens of thousands more employees than they needed. Nearly 200,000 tech workers were laid off starting in 2022 alone, according to tracking site Layoffs.fyi. The four largest tech companies, Alphabet, Amazon, Meta, and Microsoft, announced more than 50,000 combined job cuts in just a few months.

Apple was a notable exception. It grew its staff by about 20% from 2019 through 2022, far less than its peers, taking what analysts called a "more seemingly thoughtful approach to hiring."

Enter AI: the perfect excuse

Then ChatGPT launched in November 2022, and a new narrative emerged. Companies that needed to correct pandemic-era overhiring suddenly had a much better story to tell investors: "We're not shrinking. We're pivoting to AI."

Fabian Stephany, assistant professor of AI and work at the Oxford Internet Institute, has been blunt about this pattern. "I'm really skeptical whether the layoffs that we see currently are really due to true efficiency gains," he told CNBC. "It's rather really a projection into AI in the sense of 'We can use AI to make good excuses.'"

The term for this is "AI-washing", borrowed from the concept of greenwashing. Scott Dylan, founder of NexaTech Ventures, defines it clearly: companies "attribute job cuts to artificial intelligence when the real drivers are far more mundane, such as over-hiring during the pandemic boom, margin pressure, slowing consumer demand, or plain old corporate restructuring."

As Dylan puts it, "It lets companies dress up an unpopular decision in the language of progress."

The playbook in action

The pattern is remarkably consistent across industries. Here are a few examples:

Wharton management professor Peter Cappelli sees through the framing. "The headline is, 'It's because of AI,' but if you read what they actually say, they say, 'We expect that AI will cover this work.' Hadn't done it. They're just hoping. And they're saying it because that's what they think investors want to hear."

What the data actually shows

If AI were truly replacing workers at scale, we would expect to see two things: mass unemployment in AI-exposed occupations and a surge in productivity. Neither has materialized.

On job displacement: The Budget Lab at Yale University examined U.S. labor market data from November 2022 to July 2025 and found that AI hasn't yet caused widespread job losses. The occupational mix, the share of workers across different jobs, has barely shifted since ChatGPT's debut.

Research from the New York Fed echoed this finding. While 40% of service firms reported using AI in 2025 (up from 25% the year before), only 1% reported AI as the reason for laying off workers, down from 10% in 2024. Meanwhile, 35% of service firms used AI to retrain employees.

On productivity: Oxford Economics noted in a January 2026 report that "if AI were already replacing labour at scale, productivity growth should be accelerating. Generally, it isn't." Recent productivity growth has actually decelerated, a pattern more consistent with cyclical economic trends than an AI revolution.

On the scale of "AI layoffs": Data from Challenger, Gray & Christmas shows that AI was cited as the reason for roughly 55,000 U.S. job cuts in the first 11 months of 2025. That sounds alarming until you realize it represents just 4.5% of total reported job losses. Traditional "market and economic conditions" accounted for four times as many cuts (245,000). And in any given month, 1.5 to 1.8 million workers lose their jobs in the regular churn of the U.S. labor market.

Why investors reward the AI narrative

There is a simple reason companies frame layoffs as AI pivots: Wall Street likes it. Attributing staff reductions to AI adoption "conveys a more positive message to investors" than admitting to weak demand or past over-hiring, as Oxford Economics explained.

Professor Cappelli has even seen research on this dynamic taken to an extreme: companies announcing "phantom layoffs" that never actually happen, purely to get the stock price bump that comes from appearing lean and forward-thinking. "A few decades ago, the market stopped going up because investors started to realize that companies were not actually even doing the layoffs that they said they were going to do."

Layoffs based on AI's potential, not its performance

A Harvard Business Review study from January 2026, based on a survey of over 1,000 global executives, revealed something striking. AI is behind at least some layoffs, but these are "almost completely in anticipation of AI's impact." Companies are cutting jobs based on what they think AI will be able to do, not what it can do today.

As the authors put it, "the job losses and slowed hiring are real, even though companies are still waiting for generative AI to deliver on its promises." This is speculative restructuring, and it carries real risk. Gartner has reported that many companies that swapped people for AI chatbots will be "reversing course and hiring cut staffers back before long."

The real cost

The consequences of AI-washing layoffs go beyond misleading headlines.

It feeds unnecessary fear. Career expert Jasmine Escalera warns that companies framing cuts as AI-driven are "feeding the frenzy" of anxiety among workers who believe their jobs could vanish overnight. "Companies are not being honest, open and communicative about how they're implementing AI. Now companies are openly stating 'We're doing this because of AI' so it's feeding the fear."

It hurts entry-level workers disproportionately. While overall unemployment remains relatively low, the sharpest declines in hiring have hit entry-level positions, particularly in marketing, administrative, and HR roles within tech. U.S. graduate unemployment peaked at 5.5% in March 2025, though Oxford Economics argued this is more likely driven by a "supply glut" of degree-holders than by AI automation.

It obscures accountability. When companies blame AI instead of acknowledging they overhired during a pandemic bubble, nobody is held responsible for the miscalculation. As Professor Stephany frames it, "Instead of saying 'we miscalculated this two, three years ago,' they can now come to the scapegoating, and that is saying 'it's because of AI though.'"

What this means going forward

None of this means AI won't eventually reshape the labor market. It almost certainly will. But the current wave of AI-attributed layoffs is largely a story about pandemic overcorrection dressed up in futuristic language.

The honest version of most CEO layoff memos would read something like: "We hired too many people when times were good. Now we're correcting that mistake. Also, we're investing in AI." The two facts are true but mostly unrelated.

As the technology matures, there will be genuine, difficult conversations about automation and employment. But those conversations are harder to have when companies have already spent years using "AI" as shorthand for "we need to cut costs and don't want to say why."

The next time a company announces thousands of layoffs "to invest in AI," it's worth asking a simple question: Is the technology actually doing the work, or is it just doing the talking?

References