In the first quarter of 2026, 78,557 tech workers lost their jobs. Nearly half of those cuts, 37,638 positions (47.9%), were officially attributed to AI and workflow automation. It is the largest quarterly layoff total the tech industry has seen since early 2024, and if the pace holds, we could be looking at 264,730 job losses by year-end. That would surpass 2025's already painful total of 245,000.
But here is the part that deserves more scrutiny: how many of those layoffs are actually caused by AI, and how many are just branded that way?
The Q1 2026 numbers
Between January 1 and April 2026, 78,557 tech workers were laid off across the industry. 76% of affected positions were located in the United States. The companies involved range from household names to mid-size SaaS firms, but a handful of large players account for the bulk of the damage.
| Company | Jobs Cut | Stated Reason |
|---|---|---|
| Oracle | 20,000-30,000 | Shifting resources to AI data-centre capacity |
| Amazon | 16,000 | Corporate restructuring |
| Block (Square) | 4,000 (~40% of workforce) | AI replacing customer service functions |
| Microsoft | Significant (undisclosed) | AI pivot and reorganization |
| Snap, Disney, Meta, eBay, Pinterest | Various | Restructuring and automation |
The geographic concentration is striking. The Seattle area alone saw roughly 16,590 tech workers affected, driven largely by Amazon and Microsoft. San Francisco recorded 9,395 layoffs across multiple companies.
Why this wave feels different
Previous tech layoffs in 2022 and 2023 were largely about post-pandemic correction. Companies had over-hired during the boom, and the pullback was predictable.
This time, the narrative is different. Companies are not just saying "we hired too many people." They are saying "AI can do this work now." And in some cases, that is genuinely true.
Block, led by Jack Dorsey, cut 4,000 employees in February and was unusually direct about the reason. The company reported that AI systems now resolve 70-80% of customer inquiries without any human involvement. That is a concrete, measurable claim. When a company can point to specific automation metrics, the AI attribution is credible.
Customer support and service roles have been hit the hardest across the board. White-collar "computer-based" roles are increasingly in the crosshairs too. Junior and middle-skill positions are being structurally displaced, not just trimmed during a downturn but eliminated from the org chart entirely.
The AI washing problem
Here is where it gets complicated. Not every company cutting jobs has the receipts that Block does.
A survey of hiring managers found that 59% admitted their companies frame workforce reductions as AI-driven to appeal to stakeholders, even when automation played a minimal role in the decision. Let that number sit for a moment. More than half of the companies claiming "AI made us do it" are, by their own managers' admission, exaggerating.
This is AI washing, and it is happening for a simple reason: telling investors and board members that you are "restructuring around AI" sounds a lot better than admitting you over-hired, missed revenue targets, or need to cut costs.
OpenAI CEO Sam Altman has called this out directly. "There is some AI washing where people are blaming AI for layoffs that they would otherwise do," Altman said. When the CEO of the most prominent AI company in the world tells you that AI is getting too much credit for job cuts, it is worth paying attention.
Cognizant's Chief AI Officer, Babak Hodjat, put it even more bluntly: "AI becomes the scapegoat from a financial perspective, like when a company hired too many, or they want to resize, and it gets blamed on AI."
Why companies AI wash
The incentives are straightforward:
Stock price: "AI transformation" narratives tend to boost valuations. "We over-hired" does not.
Stakeholder confidence: Boards and investors want to see companies positioning for the future, not cleaning up past mistakes.
Recruitment: Paradoxically, companies that frame layoffs as AI-driven often attract more senior AI talent, because it signals they are investing in automation.
Deflection: Blaming a technology trend feels less like a management failure than admitting poor planning.
The bifurcation of the job market
One of the most important trends buried in the Q1 data is this: AI-related job postings surged 92% in Q1 2026 compared to the same period in 2025.
That is not a small number. While tens of thousands of workers are being displaced, demand for people who can build, manage, and deploy AI systems is growing fast.
What we are seeing is a bifurcation. The labour market is splitting into two tracks:
Roles being displaced:
- Customer support agents handling routine inquiries
- Junior analysts doing repeatable data work
- Mid-level administrative and operations roles
- Entry-level content and copywriting positions
Roles in high demand:
- Senior AI and ML engineers
- AI infrastructure and platform engineers
- AI product managers
- Data engineers working on training pipelines
- AI safety and evaluation specialists
The uncomfortable reality is that the people losing jobs and the people getting hired are not the same people. A customer support representative who gets laid off cannot simply pivot to building machine learning models. The skills gap is real, and retraining takes time and resources that many displaced workers do not have immediate access to.
What this means for the industry
Three things stand out to us.
First, the real AI displacement is concentrated, not universal. Companies with large customer support operations are seeing genuine automation gains. But the across-the-board narrative of "AI is replacing everyone" does not match reality. Many companies are using AI as cover for routine cost-cutting.
Second, the junior talent pipeline is at risk. If companies are eliminating entry-level and mid-level roles, where does the next generation of senior engineers and managers come from? This is a question the industry has not answered yet.
Third, geographic concentration matters. Seattle and San Francisco are absorbing a disproportionate share of these layoffs. That creates ripple effects through local economies, housing markets, and downstream service industries.
Our take
We think the truth about AI layoffs in 2026 sits somewhere between the two extremes.
Yes, AI is genuinely automating certain roles. The Block example is real. Customer support automation is measurably reducing headcount at companies that have invested heavily in it. That trend will continue and likely accelerate.
But the 47.9% figure, the share of Q1 layoffs officially attributed to AI, is almost certainly inflated. When 59% of hiring managers say their companies overstate AI's role in layoffs, we should take the headline numbers with skepticism. A meaningful chunk of these cuts are standard business restructuring dressed up in AI language.
What concerns us most is the human cost that gets lost in the narrative debate. Whether someone loses their job because of AI automation or because of AI washing, the result is the same for them. 78,557 people are navigating an uncertain job market, and the skills the market now demands look very different from even two years ago.
For workers in affected roles, the practical advice is straightforward but not easy: build familiarity with AI tools in your domain, focus on skills that complement automation rather than compete with it, and be skeptical when a company says "AI" but means "cost cuts."
For companies, we would say this: be honest about why you are making cuts. Your employees deserve that. Your investors will figure it out eventually anyway. And the AI washing trend, if it continues, risks undermining public trust in AI at exactly the moment the technology is starting to deliver real value.
The numbers from Q1 2026 are sobering. But the story they tell depends entirely on how honestly we are willing to read them.