AI drives 40 percent of May job cuts
Imagine a world where your boss doesn’t fire you because you’re underperforming, but because a machine can do your job cheaper, faster, and without complaints. That world is no longer hypothetical. In May 2025, U.S. employers announced just over 97,000 job cuts, the highest May number since the start of the Covid-19 pandemic in 2020. And for the third consecutive month, artificial intelligence was cited as the primary reason for these layoffs, accounting for almost 40% of all cuts. That’s up from 26% in April and just 7% in January. The numbers are stark: 38,579 jobs lost in May alone due to AI, according to outplacement firm Challenger, Gray & Christmas. For the year, AI-related cuts have already surpassed 87,714, more than the 54,836 recorded in all of 2024 [1] This isn’t a slow shift—it’s a rapid reshaping of the labor market, and it’s happening in real time.
The Numbers Don’t Lie—But They Don’t Tell the Whole Story
The data from Challenger, Gray & Christmas is based on company announcements of job cuts, and it paints a clear picture: AI is now the leading reason companies give for reducing their workforce. However, the data only captures publicly disclosed cuts, which may underrepresent the true scale of AI-related displacement In May, AI accounted for almost 40% of all announced layoffs, up from 26% in April. The technology sector led the way, with 38,242 total cuts in May alone. But not all economists take these announcements at face value. Daniel Zhao, chief economist at Glassdoor, warns that companies may be “scapegoating” AI to justify layoffs that have other causes, such as restructuring or cost-cutting. “A company can say [AI] is why we’re doing layoffs, but that doesn’t necessarily mean that’s actually why those layoffs are happening,” he says. [2] This skepticism is echoed by Fabian Stephany, assistant professor of AI and work at the Oxford Internet Institute, who notes that some firms may be using AI as a convenient excuse to downsize without facing backlash.
Despite these caveats, the trend is undeniable. The percentage of layoffs attributed to AI has risen sharply—from 7% in January to 10% in February, 25% in March, 26% in April, and now almost 40% in May. This acceleration suggests that AI adoption is moving from experimental to operational across many industries. Companies are not just talking about AI—they are acting on it. Coinbase CEO Brian Armstrong announced in May that his company was cutting 14% of its workforce, attributing the move in part to AI. “Over the past year, I’ve watched engineers use AI to ship in days what used to take a team weeks,” he said in a memo to employees. “Non-technical teams are now shipping production code and many of our workflows are being automated. The pace of what’s possible with a small, focused team has changed dramatically, and it’s accelerating every day.”
Where AI Lifts: The Other Side of the Coin
While AI is driving job cuts in some areas, it’s also creating new opportunities—but these opportunities are not evenly distributed. The tech sector, which leads in layoffs, also leads in hiring. In May, tech companies announced 11,250 planned hires, followed by electronics with 3,158 and insurance with 1,435. This suggests that AI is reshaping the labor market rather than simply shrinking it. “Many companies are changing how they are allocating resources in response to AI,” says Daniel Zhao. This reallocation means that some jobs are being replaced, but others are being created—often in roles that require new skills, such as AI development, data analysis, and machine learning engineering.
But the jobs that are being created are not the same as the jobs that are being lost. Thomas Thompson, chief economist at Havas Edge, points out that “someone who was an engineer in biopharmacy and had their job replaced with AI isn’t going to be interested in a logistic warehouse job.” This mismatch between the skills of displaced workers and the demands of new roles is a growing concern. The Bureau of Labor Statistics reported that U.S. payrolls rose by 172,000 in May, far exceeding expectations, but this growth is concentrated in sectors such as healthcare, hospitality, and logistics, which are not easily accessible to workers from industries heavily impacted by AI. For example, healthcare, hospitality, and logistics are hiring, but these fields often require different training or certifications than those held by displaced tech workers.
The Deception: Companies Using AI as a Justification
One of the most troubling aspects of this trend is the possibility that companies are using AI as a smokescreen for other motives. “I’m really skeptical whether the layoffs that we see currently are really due to true efficiency gains,” says Fabian Stephany. “It’s rather really a projection into AI in the sense of ‘We can use AI to make good excuses.’” This is not a new phenomenon. Throughout history, companies have used technological change as a rationale for layoffs that were actually driven by cost-cutting, shareholder pressure, or poor management. The difference now is that AI is a powerful narrative—it sounds forward-thinking and inevitable, making it harder for workers to push back.
The data supports this skepticism. While AI-related layoffs have surged, overall job cuts in 2026 are running roughly even with 2024 levels when you strip out the distortions caused by federal workforce reductions in 2025. This suggests that AI is not causing a dramatic increase in layoffs overall, but rather changing the mix of who is being laid off and why. Companies that might have previously cited “restructuring” or “market conditions” are now pointing to AI, perhaps because it sounds more strategic or less blameworthy. This deception is dangerous because it masks the real reasons behind job losses and makes it harder for policymakers to address the underlying issues.
Where AI Makes Us Superfluous: The Human Cost
The most alarming aspect of this trend is the human cost. For the workers who lose their jobs to AI, the experience is deeply personal and often devastating. Even if the overall labor market is “humming along just fine,” as Columbia Business School associate professor Daniel Keum puts it, the impact on individuals and communities is real. Workers who have spent years building skills in fields like software development, data entry, customer service, and even some forms of engineering are finding that their expertise is no longer valued. The jobs that remain often require different skills, leaving many workers feeling obsolete.
This feeling of superfluousness is not just about losing a paycheck—it’s about losing a sense of purpose and identity. For decades, work has been a central part of how people define themselves. When that work is taken over by a machine, it can lead to anxiety, depression, and a loss of social connection. The pace of change is accelerating. In 2023, AI was barely mentioned in layoff announcements. By 2025, it accounted for 54,836 cuts. In just the first five months of 2026, that number has already surpassed 87,714. If this trend continues, millions of workers could be displaced in the coming years.
The Lock-In: How AI Companies Are Building Walls
Beyond the layoffs, there is a deeper concern about how AI companies are positioning themselves to control the future of work. Samuel Colvin, CEO of Pydantic, a company that works closely with OpenAI and Anthropic, explains that these frontier labs are shifting their strategies from competing on model quality to locking customers into their ecosystems. “A year ago, what they cared about was revenue,” he says. [3] “Now when one assumes they’re both trying to IPO, their profit margin becomes really important. And if you want a margin, then what you don’t want is to compete just on model quality because at that point you need to spend masses of money training the best model and you need to provide inference on that model as cheaply as possible.”
This shift is driving the development of tools like Claude Code and Codex, which offer discounted subscriptions to encourage heavy usage. The goal is to create code bases that are so large and complex that they can only be maintained by the same AI tools that generated them. “Once customers have these enormous code bases, which would be basically written AI, you get to a point where you can’t maintain them as a human,” Colvin warns. “If I’ve used AI to generate 20,000 lines of code overnight, I can use a model to go and fix that, but as a human, I can’t ever go and maintain that code.” This creates a lock-in effect where corporate customers must keep using these AI services, and once they are locked in, prices will likely rise.
Colvin predicts that these companies will soon offer additional services, such as storing the full exchange between users and the AI model as it writes code. This would allow developers to look up the intent behind any line of code, but the data would be non-exportable. “So now you’re locked into whoever you’re using for that across the whole business,” he says. This is a form of deception—offering convenience and efficiency in exchange for long-term dependency. For workers, this means that even if they keep their jobs, they may find themselves increasingly reliant on tools that they cannot fully control or understand.
The Data Behind the Story: How the Numbers Were Collected
The Challenger, Gray & Christmas report is based on company announcements of job cuts, which are tracked by the firm’s analysts. This methodology has limitations. Companies may not always be transparent about the reasons for layoffs, and some may choose not to announce them at all. Additionally, the data only captures cuts that are publicly disclosed, which means the true number of AI-related job losses could be higher. The firm has been tracking layoffs since 1993, and it added AI as a specific category in 2023. This relatively new category makes it difficult to compare current trends with historical data, but the trajectory is clear: AI is becoming an increasingly common justification for workforce reductions.
The report also tracks hiring plans, which provide a more nuanced picture. In May, employers announced 80,742 planned hires, which is described as “historically low by prepandemic standards.” This suggests that while some sectors are growing, the overall pace of hiring is not keeping up with the pace of layoffs. For workers, this means that even if they are not directly affected by AI-related cuts, they may face a tighter job market with fewer opportunities.
What Comes Next: The Future of Work Under AI
The question on everyone’s mind is: what comes next? If AI continues to be the leading reason for job cuts, we could see a fundamental shift in how work is organized. Some economists predict that AI will create new jobs in fields like AI ethics, data curation, and human-AI collaboration. But these roles may not be enough to absorb the millions of workers who are displaced from traditional jobs. The skills required for these new roles are often highly specialized, and the transition may leave many workers behind.
Daniel Zhao advises job seekers to “diversify their approach” and explore other fields. “I think many people focus on the industries or the jobs where they’ve worked in the past,” he says. “But many of those skills are applicable across many different fields.” This advice is sound, but it is easier said than done. Retraining takes time and money, and not everyone has access to the resources needed to make a career change. For older workers, the challenge is even greater, as age discrimination and the cost of upskilling can be prohibitive.
The Human Cost of Inaction
The most important takeaway from this data is that ignoring the trend will have real consequences. If companies continue to use AI as a justification for layoffs without investing in retraining and support for displaced workers, we risk creating a permanent underclass of people who are unable to find meaningful work. The labor market is being reshaped in real time, and those who are not prepared will be left behind. This is not a problem that will solve itself—it requires deliberate action from policymakers, businesses, and educational institutions to invest in retraining, social safety nets, and ethical AI deployment
For now, the message is clear: AI is not just a tool for innovation—it is also a tool for displacement. The numbers show that it is already reshaping the labor market in ways that are both promising and alarming. The challenge is to harness its potential while mitigating its harms. If we fail to do so, the human cost will be measured not just in job losses, but in lost opportunities, broken communities, and a widening gap between those who can adapt and those who cannot. The future is being written now, and the choice is ours to make.
Sources
1. Challenger, Gray & Christmas
3. Pydantic
4. Anthropic