AI Drives 40% of US Job Cuts in May as 97,000 Positions Eliminated

Artificial intelligence is now the single biggest reason American companies give for cutting jobs. In May 2026, AI was cited in 38,579 job cuts — 40% of all layoffs announced — marking the third consecutive month it has been the top reason for workforce reductions, according to the Challenger, Gray & Christmas report released June 4.

U.S. employers announced 97,006 total job cuts in May, up 16% from April's 83,387 and the highest May total since the pandemic‑hit 2020, when 397,016 cuts were recorded. "AI is now the leading reason companies give for cutting jobs, and the primary industry citing it is technology," Andy Challenger, the firm's chief revenue officer, said in a statement reported by Yahoo Finance.

The technology sector announced 38,242 job cuts in May — the highest monthly total for the industry since August 2024. For the year, tech has shed 123,653 jobs, a 66% increase from the 74,716 cuts in the same period of 2025. Technology remains "the leading job cutter of 2026 by a wide margin," according to Challenger.

FinTech companies announced 5,731 cuts in May, the bulk citing AI. Pharmaceutical firms cut 5,045 positions. Transportation shed 6,909 jobs, bringing its year‑to‑date total to 40,388 — a 449% surge from the same period last year.

But the numbers aren't entirely bleak. As Yahoo Finance noted, the tech sector also led hiring plans in May. And year‑to‑date, 2026's 397,755 cuts are down 43% from the 696,309 announced through May 2025 — though the 2025 numbers were inflated by massive federal workforce reductions under DOGE.

Beyond the current numbers, a separate Mercer Global Talent Trends report released in late May found that 99% of nearly 1,000 U.S. executives surveyed expect AI to lead to at least some headcount reduction in the next two years, and 98% are preparing major workforce restructuring plans around AI adoption.

As Gizmodo reported, only 32% of executives said they believed the workforce can optimally combine human and machine capabilities — meaning two‑thirds of CEOs surveyed see AI and human workers as largely incompatible. Employee wellbeing is declining in parallel: only 44% of workers reported thriving at work in 2026, down from 66% in 2024, with AI‑driven job anxiety cited as the primary cause.

The AI‑driven cuts are disproportionately hitting entry‑level and early‑career positions. The reasoning, according to multiple studies cited by,¹ is that AI is best at automating simpler tasks that early‑career workers would typically perform as on‑the‑job training. But the effect is that companies are "saying to hell with early‑career workers and training the future of the workforce."

The result has been what the New York Times described as the grimmest job market for 22‑to‑27‑year‑olds since the pandemic. A Stanford study, as cited by,¹ found AI is already "crushing the early‑career job market," ¹ and Gen Z's use of AI is plateauing as the cohort reports increasing anxiety and anger over the technology.

The numbers contain an important tension. On one hand, AI‑attributed cuts are accelerating — AI went from 7% of all layoffs in January to 25% in March, 26% in April, and 40% in May. The 38,579 AI‑attributed cuts in May was the highest monthly total since Challenger began tracking the category in 2023. For the full year, AI has been cited in 87,714 cuts, already surpassing the 54,836 attributed to it in all of 2025.

On the other hand, official government data tells a less dramatic story. Yahoo Finance noted that overall layoff rates remain low per Bureau of Labor Statistics data, and continuing claims for jobless benefits are tracking below last year's levels. Goldman Sachs estimates AI is causing a net loss of 16,000 U.S. jobs per month — meaningful but not apocalyptic.

"AI isn't yet the jobpocalypse some predicted," Challenger said in the May 2026 Challenger Report. "Like spreadsheets and email before it, the technology will ultimately make workers more productive, but our data shows companies are already acting on it. The open question isn't whether AI changes the workforce, but how fast."

Beyond AI‑specific cuts, the Challenger report identified a sharp rise in layoffs tied to mergers and acquisitions and bankruptcy‑related losses. "Companies are restructuring aggressively as they reposition for an AI‑driven economy," Challenger said.

Notable examples include Wix, which cut 20% of its workforce and then lowered its 2026 outlook less than two weeks later, as reported by Ctech. Israeli startup Hailo cut 50% of its workforce amid funding pressure. SuperOps, a SaaS startup, reportedly laid off nearly 30% of staff, igniting what some are calling "India's biggest tech debate" over AI‑first versus workforce‑first strategies.

At the same time, Binance is ramping up AI hiring with 380+ new AI‑linked roles opening globally, according to CryptoRank — a reminder that AI is also creating demand for new skills, even as it eliminates old roles.

The data has several implications for people building with AI:

• AI skills are both shield and target: Companies are cutting roles that AI can automate while hiring for roles that build and deploy AI. The 380+ new AI roles at Binance and Meta's new Workforce Academy to train data center workers, reported by WSJ, show where demand is shifting.
• Entry‑level is the canary: If you're early in your career, the jobs that used to be stepping stones — basic coding, content creation, data entry — are the ones AI is absorbing fastest. The path forward involves specializing in what AI cannot yet do: systems design, creative direction, and AI orchestration itself.
• The CEO consensus is real: When 99% of nearly 1,000 executives say they expect AI layoffs within two years, it's not speculation — it's a signal of intent. Companies that haven't yet announced AI‑related restructuring likely will.
• The counter‑narrative exists: The Linux Foundation reports AI is actually boosting demand for tech talent. Goldman Sachs' estimate of 16,000 net monthly job losses is 0.01% of the U.S. workforce. The real story is transformation, not elimination — but transformation that is deeply uneven and painful for those caught in the transition.