One of the biggest questions raised by artificial intelligence is to what degree it will eliminate jobs, and when that displacement will start. Anthropic CEO Dario Amodei famously predicted AI could wipe out half of entry-level white collar roles by 2030. Others have been more optimistic, saying that, like past technological shifts, it will ultimately create as many jobs as it replaces.
But for many tech workers, the shake-up has already begun. Salesforce eliminated 4,000 customer support roles last year, citing efficiency gains from its agentic AI product. Goldman Sachs and Hewlett-Packard have made similar moves, with HP stating its AI initiatives will result in as many as 6,000 job cuts by 2028. Meanwhile, Duolingo announced it would stop using human contractors for work AI can handle, and that it is only hiring for positions that cannot be further automated. And Klarna, which shed 40 percent of its workforce due to an AI-motivated hiring freeze, expects to trim another 33 percent of its staff by 2030.
What Is AI Washing?
Broadly speaking, AI washing refers to companies overstating or misrepresenting how extensively they use artificial intelligence. In the context of layoffs, it means attributing financially motivated job cuts to AI efficiencies that don’t yet exist or aren’t fully implemented.
All told, employers announced more than 1.2 million job cuts in 2025 — the most since 2020 — and AI was cited in nearly 55,000 of them, or 4.5 percent, according to research firm Challenger, Gray and Christmas. One of the biggest layoffs of the year came from Amazon, which slashed a total of about 30,000 corporate jobs. CEO Andy Jassey initially touted the company’s use of generative AI and AI agents as a means of reducing its workforce, but later clarified that these cuts were “not really AI-driven, not right now at least.”
After reading through quarterly earnings reports and investor calls, one might think that workers are already being replaced by AI tools that can do their jobs for them. But in reality, AI’s current capabilities often fall short of the disruption tech executives typically convey when justifying mass layoffs. Today’s systems can transcribe meeting notes, generate code and automate back-end business processes, but they are far from replacing entire departments, leading some skeptics to question whether companies are simply using AI as a convenient cover — a practice critics call “AI washing.”
The Rise of AI Washing
Similar to misleading marketing practices like greenwashing or rainbow washing, “AI washing” was originally used to call out companies claiming to use artificial intelligence when they really weren’t. But lately, the term has shifted to describe when a company disingenuously blames AI to explain away job cuts and other unpopular business decisions, even when the full picture is far more complicated.
“Financially driven layoffs are being confused with AI-driven layoffs,” market research firm Forrester wrote in its latest AI Job Impact Forecast. “Many companies announcing AI-related layoffs do not have mature, vetted AI applications ready to fill those roles, highlighting a trend of ‘AI washing’ — attributing financially motivated cuts to future AI implementation.”
Other experts have suggested AI layoffs could be premature, possibly misleading. Sixty percent of the more than 1,000 executives surveyed in another study said they made headcount reductions in anticipation of AI efficiencies. Another 29 percent reported hiring fewer people than normal. Only 2 percent said they had made large staff reductions as a result of actual AI implementation.
This practice has been around for years, but has been gaining renewed attention in recent months. The term “AI washing” was even used by OpenAI CEO Sam Altman, who agreed that some companies are blaming unrelated layoffs on the technology.
And the AI washing trend may continue into 2026. Nearly 60 percent of U.S. hiring managers surveyed by Resume.org said they plan to conduct layoffs in 2026, and AI or automation was the most-cited reason. At the same time, only 9 percent said AI has fully replaced certain roles, while 45 percent said it has partially reduced the need for new hires. Nearly 60 percent said they emphasize AI’s role in reducing hiring or cutting jobs because it’s viewed more favorably than financial constraints.
Why Are Companies AI Washing?
Peter Cohan, an associate professor of management practice at Babson College, told Built In that employees cite AI in their layoff announcements because it is “the least bad reason companies can use.”
If a company blames layoffs on tariffs, for example, it risks being attacked by the Trump administration. If a decrease in sales is cited as a reason, investors may sell off their stock. But blaming AI makes the company seem more forward-thinking and innovative, essentially turning bad news into good news. Cohan noted hot topics like the pandemic, tariffs and AI are often used in earnings reports to explain away business challenges, saying they can be “a safe thing to hide behind.”
Some experts have also suggested that AI job cuts could be caused by a right-sizing in the tech sector’s labor market. During the post-pandemic hiring boom of 2021, tech companies flush with venture capital and growth ambitions outbid each other to attract job-hopping tech professionals. Many companies overhired, as their plans to scale were cut short by the market contraction that followed.
“Many organizations went overboard on hiring during the pandemic and post-pandemic. There was never enough demand to justify that,” Manish Jain, principal research director at Info-Tech Research Group, told Built In. “Now, with AI as the façade, many, if not all, are happy to offload a large number of people.”
Is AI Actually to Blame Here?
Artificial intelligence does appear to be slowing down hiring in certain corners of the labor market, particularly customer support, software engineering and entry-level white-collar roles. A Stanford University study found employment among early-career workers in AI-exposed occupations has dropped 16 percent since the launch of ChatGPT in 2022, suggesting that this technology is reshaping the bottom rung of the career ladder rather than hollowing out entire departments — at least for the time being.
Zoom out, however, and the broader job market looks far less disrupted. A study by Yale University’s Budget Lab found no overall change in employment for workers in AI-exposed occupations. A National Bureau of Economic Research survey similarly found that AI had little measurable impact on employment or productivity thus far. But over the next three years, respondents said they expect it to boost productivity by 1.4 percent and to reduce employment by 0.7 percent — still hardly the kind of shockwave implied by some industry leaders. Research from Oxford Economics’ also notes that the 55,000 AI-related cuts cited in the Challenger, Gray and Christmas report account for just 4.5 percent of total layoffs, and that the sluggish hiring market for early-career professionals could be due to a “supply glut” of young professionals with college degrees.
Companies citing AI as a reason for layoffs may be a bit premature. While chatbots like ChatGPT generated a lot of hype, most companies didn’t start to integrate them on an organizational level until years later. It has taken some time for companies to understand the capabilities of AI and implement these technologies in a safe, reliable way. Even now, most organizations don’t feel comfortable completely outsourcing business functions like customer service or legal support to AI just yet.
“A lot of those implementation details would have to be absolutely bulletproof before anybody would want to trust their lives with that,” Cohan said. “There’s a huge gap between the ease of saying something and the difficulty of making it happen.”
That doesn’t mean AI lacks capability, though. Max Leaming, head of data science and AI solutions at Manpower Group, told Built In that it “is more capable than a lot of people have not just realized, but are willing to admit.” Thanks to vibe coding, a software engineer can now build and test an app in about an hour, a task that he said would have ordinarily taken three weeks. And AI tools are creeping into domains like financial analysis and legal research as well. More and more professionals are starting to adopt this technology to boost their productivity, but Leaming said that productivity is difficult to quantify.
While AI might be effective at augmenting certain roles and boosting efficiency here and there, Cohan said it’s still “not obvious” — at least not at this point — how AI will create a “quantum value leap,” as he calls it, that would motivate a business to undergo a significant organizational restructuring.
“These uses of AI right now strike me as things that cut costs, but what creates value… is expectations-beating growth,” Cohan said. “I'm not really seeing companies using AI to create massive, expectations-beating growth, with a few exceptions,” adding that Google and Meta are using AI to drive revenue growth in their core advertising business.
Will AI Cause More Layoffs In the Future?
None of this is to say that AI won’t displace, restructure or outright eliminate millions of jobs in the future.
Forrester predicts this technology will eliminate 10.4 million jobs — a 6 percent reduction — by 2030. That estimate, which would surpass the job loss seen during the Great Recession of 2008, is somewhat conservative compared to other estimates. A Goldman Sachs report from 2023 estimated 300 million jobs would be exposed to AI by 2030, but that most of those jobs will be complemented by automation, not necessarily replaced. A report from the World Economic Forum, meanwhile, predicted AI will displace 92 million jobs by 2030, but it will also create 170 million jobs, resulting in a net increase of 78 million jobs — a 7 percent increase from current levels.
With hundreds of millions of jobs hanging in the balance, some federal lawmakers have sought more concrete data about AI’s impact on the workforce. A proposed bill in the U.S. Senate aims to quantify AI’s impact on the workforce by requiring federal agencies, public companies and some private companies to provide data about how many roles are eliminated, added or left unfilled due to AI. Employers would also have to quantify how many employees are retrained due to AI adoption. The bill, which has not been scheduled for a vote yet, is one of several efforts underway to gain a more accurate accounting of AI’s impact on the job market.
But pinning down AI’s impact on employment can be complicated for all sorts of reasons. It’s not only difficult to quantify, but it also relies on self-reporting from companies that have their own motives. Since March 2025, when New York gave employers the option to cite “technological innovation or automation” in legally required layoff notices, Wired found that none of the 160 companies filing notices — including Amazon, Goldman Sachs and others that cite AI efficiencies in other communications — checked the box attributing layoffs to AI.
While we may not have accurate data as to the real-world impact of AI, it’s clear that the technology has not yet had the type of sweeping impact that would push humans out of the workforce entirely. And when executives “AI wash” their layoff announcements, they may be revealing that they view AI as a means for eliminating jobs, which could cause workers to not trust — or even sabotage — their future plans for AI adoption.
Frequently Asked Questions
Is AI causing widespread layoffs?
Not broadly. While some companies cite AI in layoff announcements, AI-linked cuts accounted for only about 4.5 percent of total layoffs in 2025, according to Challenger, Gray & Christmas. Most evidence suggests AI’s labor impact so far is limited and uneven.
Why would companies blame layoffs on AI instead of other factors?
AI can be a safer and more favorable explanation than alternatives like weak demand, overhiring or business missteps. Framing layoffs as AI-driven may signal innovation to investors and avoid political or market backlash.
Is AI affecting certain types of work more than others?
Yes, early-career and entry-level, white-collar workers — particularly in customer support and software programming — may be more exposed to early AI-related slowdowns in hiring and job cuts.
