What happened
AI layoffs have become the defining workforce story of 2026, and the latest name on the list is monday.com. The project-management software company announced it is cutting 20% of its staff — roughly 630 people — while its own SEC filing points to a shift toward a "leaner, more focused operating model" built around an "AI-driven growth strategy." What makes the announcement strange is the timing: monday.com's revenue grew 24% year-over-year to $351 million, and the company projects 19-20% growth for the full year. This isn't a company in distress trimming costs to survive — it's a growing business citing AI as the reason for cutting people anyway.
monday.com is now the 21st major tech company in 2026 to name AI as a factor in layoffs, according to a running tracker maintained by TechCrunch. And the trend behind that list is accelerating fast. Outplacement firm Challenger, Gray & Christmas reports that AI was cited as the reason for 7% of announced U.S. layoffs in January, 25% in March, 26% in April, and a record 40% in May — 38,579 jobs in a single month. June saw a slight pullback to 31%, but AI still ranked as the number one cited cause for layoffs for a fourth consecutive month, the longest streak on record. Over the first half of the year, 101,743 layoffs have been attributed to AI — nearly double the total for all of 2025.
Why it matters
The tech sector is ground zero. U.S. tech companies have cut almost 140,000 jobs since the start of the year, more than a third of all announced layoffs nationwide. Amazon, Oracle, Microsoft, and Meta alone account for roughly 50,000 of those cuts — about 6% of their combined corporate headcount. On paper, the logic tracks: the same companies are pouring record sums into AI infrastructure, with Amazon, Alphabet, Meta, and Microsoft expected to spend around $725 billion on data centers this year. Cutting payroll frees up cash for the build-out.
But one number doesn't fit that story. The share of layoffs attributed to AI grew more than fivefold in four months, while the underlying technology didn't make a comparable leap — model improvements over that stretch were incremental, not revolutionary, and no company demonstrated a rollout dramatic enough to explain a jump like that. That leaves two explanations: either AI suddenly got far better at replacing workers than anyone can point to, or companies changed how they talk about layoffs rather than what's actually driving them.
Markets seem to be betting on the second explanation. Stocks of companies that blamed AI for layoffs underperformed the Nasdaq by nearly 10% over the following 30 trading days — compared to just a 4% lag for companies that cited other reasons. To investors, "we're cutting because of AI" doesn't read as "we got more efficient." It reads as "we have a problem and found a tidy way to explain it." CNBC's review of 23 S&P 500 companies that announced AI-related layoffs found 13 traded lower afterward, with an average drop of about 25% among the losers — including Nike, Salesforce, and Fiverr.
How to use it today
For business leaders, the practical lesson isn't to avoid AI — it's to be honest about what it's actually doing inside your organization before making it your public explanation for cuts. A Gartner survey of 350 executives at large companies found that AI-driven layoffs don't reliably make companies more efficient. The best results came from companies that used AI to augment existing employees rather than replace them outright.
That distinction matters for anyone building an AI adoption plan. If you're a founder, marketer, or team lead experimenting with AI tools, the smarter move is pairing automation with skill redistribution rather than headcount reduction as a first step. Testing free, accessible AI tools like the ones available at [mykreatool.com](https://mykreatool.com) is a low-risk way to see where automation genuinely saves time — content drafts, image generation, quick data tasks — before deciding whether it changes staffing needs at all. Companies that treat AI as a productivity multiplier for existing teams, rather than a replacement narrative, are the ones showing up on the right side of Gartner's efficiency data.
Who benefits
The picture inside individual companies is messier than the layoff headlines suggest. Meta cut 8,000 jobs but simultaneously moved 7,000 employees into new AI-related roles. IBM is tripling its hiring of junior engineers for AI-focused teams even as it restructures elsewhere. Oracle, which cut 21,000 people (13% of its workforce) over 12 months, hedges its language in its annual report: "the adoption of AI technologies has resulted, and may continue to result, in workforce reductions."
That pattern points to a real beneficiary group: workers and companies that reposition around AI-adjacent skills rather than resist them. Jobs aren't simply vanishing — they're being redistributed toward AI-integration, data, and oversight roles, even while press releases keep the single word "AI" front and center.
Risks
The biggest risk is treating self-reported layoff statistics as proof of AI's real-world impact. Challenger's numbers count what employers say, not what AI actually replaced — the 40% figure from May reflects the share of companies citing AI as a reason, not the share of jobs AI verifiably eliminated. OpenAI's Sam Altman himself has acknowledged this gap in the public narrative.
For businesses, the reputational risk cuts both ways: blaming AI for layoffs when the real driver is overspending on infrastructure or slowing growth invites market skepticism, as the stock underperformance data shows. And for employees, treating AI-related layoff headlines as evidence of unavoidable mass displacement can lead to premature panic rather than a clear-eyed look at which specific tasks are genuinely at risk.
Conclusion
The headline numbers are real — 101,743 U.S. jobs tied to AI in layoff announcements through the first half of 2026, a fourth straight month of AI as the top cited cause, and 21 companies now on record. But the data underneath complicates the simple story. Markets are penalizing companies that use AI as a layoff excuse, internal reshuffling often accompanies the cuts, and the efficiency gains only show up when AI augments people rather than replaces them. The real story of 2026 isn't that AI is quietly firing the workforce — it's that "AI" has become the most convenient line in a corporate press release.
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