Monday.com has become the latest technology company to connect a major layoff to its AI strategy, adding another data point to a 2026 pattern in which established software and platform vendors are cutting staff while redirecting spending toward AI products, infrastructure, and internal automation.

According to TechCrunch, the work management company disclosed in an SEC filing that it plans to reduce its workforce by about 20%, or a little more than 600 employees. The company described the move as part of a restructuring tied to changes in product, marketing, and go-to-market execution, and said the effort supports a leaner operating model as it continues to invest in an “AI-driven growth strategy.” For AI builders and enterprise buyers, the significance is less about one company’s headcount change than what it says about the current operating logic across the sector: AI is no longer just a product roadmap line item; it is increasingly being used to justify organizational redesign.

Monday.com’s own framing is more nuanced than a simple automation-equals-job-cuts story. TechCrunch reported that co-founder Eran Zinman told employees in a LinkedIn memo that the layoffs were “not made to reduce costs or replace people with AI,” but rather to adapt the organization to an AI-first vision the company began laying out about a year earlier. That distinction matters, even if workers and investors may view it skeptically. In many cases this year, companies have presented AI as a reason to flatten management, consolidate teams, and shift hiring toward infrastructure and model-adjacent roles rather than as a direct substitute for every eliminated job.

What Monday.com actually disclosed

The clearest confirmed facts come from Monday.com’s regulatory filing as described by TechCrunch. The company expects net restructuring charges of $45 million to $55 million. At the same time, it still projects as much as 20% year-over-year revenue growth for 2026, suggesting the cuts are not being presented as a response to immediate business deterioration.

That combination is important. When a company cuts deeply while still guiding for growth, it usually signals a belief that future growth will come from a different operating structure than the one built for the previous product cycle. In Monday.com’s case, the stated driver is its broader AI repositioning. The company had already rebranded around a platform-wide AI push, according to TechCrunch’s account, and this week’s layoff announcement appears to be an extension of that strategy rather than an isolated cost exercise.

Still, there are limits to what can be concluded from the available evidence. Monday.com has not, based on the source material here, publicly broken down which functions are most affected, how many roles may be rehired in AI-related areas, or what specific product investments the restructuring will accelerate. That leaves a gap between the strategic language and the operational reality that builders, customers, and investors will want to monitor.

A broader 2026 trend across Big Tech and enterprise software

TechCrunch’s running tally places Monday.com inside a much larger wave. The publication points to Financial Times analysis showing that U.S. tech companies have cut nearly 140,000 jobs since the start of 2026, with Amazon, Oracle, Meta, and Microsoft accounting for almost 50,000 of those reductions while investing heavily in AI infrastructure.

The individual cases vary, but the pattern is consistent. Oracle said in a financial filing that adoption and deployment of AI technologies across its operations have resulted, and may continue to result, in workforce reductions. GitLab said it was laying off about 14% of staff to fund AI infrastructure investment and support demand from AI workflows. Intuit said it was reducing complexity and reallocating resources toward AI. Cisco said its cuts were about realigning around silicon, optics, security, and AI rather than pure savings. Snap explicitly cited AI advancements as enabling teams to reduce repetitive work and increase velocity.

Even the cases with more ambiguous public explanations tend to circle back to the same operating model shift. Microsoft, according to TechCrunch, said certain role eliminations were not being directly replaced by AI, while also acknowledging that AI is changing how work gets done and that headcount is expected to keep declining. Meta reportedly cut about 8,000 employees while moving roughly 7,000 into AI-focused roles, illustrating that “layoffs because of AI” often means a reallocation of labor toward model development, infrastructure, and AI productization rather than a clean one-way replacement.

For companies such as Google and Cloudflare, the pattern extends beyond engineering. Google’s cuts reportedly included management compression and rolling restructuring in Cloud and security-related teams. Cloudflare’s CEO said the majority of affected staff were in management and support functions. That matters because the first labor impact of enterprise AI may not be software engineers writing code, but the administrative, coordination, review, and middle-layer roles around them.

Evidence, benchmarks, and where the claims are weak

The strongest evidence in this story comes from public filings and named executive statements cited by TechCrunch. Monday.com’s workforce reduction, expected restructuring charges, and growth outlook are reported as filing-based facts. Similar weight applies to Oracle’s disclosure, Snap’s SEC-filed memo, and executive commentary attributed to named CFOs and CEOs at companies including Microsoft and Cisco.

But the more sweeping narrative claims deserve caution. The headline idea that companies are “blaming AI” for layoffs is partly a media interpretation built from company language that ranges from direct to highly qualified. Some companies explicitly cite AI adoption as a factor; others say AI is changing workflows while also pointing to restructuring, management simplification, investment priorities, or market conditions. Those are related but not identical claims.

There is also an important market signal in the Financial Times analysis referenced by TechCrunch: companies citing AI as a factor in layoffs reportedly underperformed the Nasdaq by almost 10% in the 30 trading days after their announcements. That does not prove management teams are overstating AI’s role, but it does suggest investors are not uniformly rewarding these announcements as evidence of greater efficiency or stronger strategy.

The counterevidence is equally notable. TechCrunch says AI-native employers including Anthropic and OpenAI are hiring rapidly, and that IBM says it is increasing entry-level hiring in AI and hybrid-cloud roles alongside cuts elsewhere. That complicates any simplistic conclusion that AI only destroys jobs. Based on the available reporting, the more defensible claim is that AI is changing the mix of jobs, the location of investment, and the tolerance for organizational layers.

What this means for builders and enterprise buyers

For product teams, Monday.com’s move is another sign that AI strategy now reaches far beyond adding copilots or workflow assistants. Companies are redesigning org charts around faster software delivery, lower coordination overhead, and more concentrated investment in infrastructure. Builders should assume that future roadmaps will be judged not only on feature adoption, but on whether AI materially changes support burden, implementation speed, and margin structure.

For enterprise AI buyers, the practical question is reliability during transition. Layoffs tied to AI strategy can improve focus, but they can also disrupt product support, account management, services, and roadmap continuity. A customer evaluating Monday.com, GitLab, Oracle, or Google in this environment should ask who remains accountable for implementation, security, integrations, and change management after restructuring. A vendor’s AI vision matters less if the reorganization weakens delivery.

There is also a labor-market signal for founders and researchers. Demand appears to be shifting toward people who can build or operate AI systems at scale: platform engineers, inference and data infrastructure specialists, applied researchers, and product leaders who can turn model capability into measurable workflow gains. Meanwhile, coordination-heavy roles and conventional management layers look increasingly exposed where companies believe AI tools can compress review cycles and decision-making.

The result is a sharper divide inside enterprise AI. On one side are vendors investing aggressively in models, infrastructure, and AI product experiences. On the other are customers asking whether those investments produce net-new value or simply justify cost cutting. Monday.com is now part of that tension.

What to watch next

First, watch whether Monday.com follows this restructuring with specific product releases, pricing changes, or usage metrics tied to its AI push. Without that, the company’s explanation remains strategic intent rather than demonstrated execution.

Second, monitor whether peers such as Microsoft, Meta, Oracle, GitLab, and Cisco disclose clearer links between AI investments and operating results. Investors will want evidence that lower headcount and higher AI spending produce faster product cycles, stronger customer retention, or better margins.

Third, pay attention to where hiring resumes. If companies continue cutting in legacy functions while expanding roles in AI infrastructure, model operations, and applied product teams, that will reinforce the idea that this is a workforce reallocation story as much as a replacement story.

Finally, watch enterprise sentiment. If buyers begin to see service degradation or roadmap instability after these restructurings, the market may become less tolerant of “AI-first” explanations for layoffs, especially when vendors are still posting growth.

Creati.ai perspective

Monday.com’s announcement matters because it shows how thoroughly AI has moved from experimental feature set to organizing principle for software companies. The story is not just that a vendor is building AI into its product. It is that management believes the company itself must be rebuilt around AI, from go-to-market structure to staffing model.

That does not automatically make the strategy wrong, and it does not prove AI directly replaced the eliminated jobs. But it does reveal a harder truth for the market: in 2026, “enterprise AI” increasingly means organizational compression, capital reallocation, and a demand for teams that can ship more with fewer layers. For builders, that raises the bar on measurable usefulness. For buyers, it raises the bar on vendor stability. And for the broader sector, it suggests the next phase of AI competition will be judged as much by operating discipline as by model demos.