On May 5, Freshworks Inc. filed a restructuring plan with the Securities and Exchange Commission that contained a phrase almost no public company would have put in a regulated disclosure two years ago. The San Mateo-based software maker said it would “increase leverage of AI and automation across the business,” directly linking a round of job cuts to machines now capable of performing work humans once did. Two days later, Cloudflare followed with its own filing, disclosing a workforce reduction of roughly 20% and estimated charges between $140 million and $150 million as part of what it called an operating-model shift.
These are not leaked Slack messages. They are formal SEC filings made under penalty of securities law. And they signal something that has been building for months: artificial intelligence is no longer just an executive talking point used to explain away headcount cuts. It is now a stated rationale in the documents companies are legally required to get right.
Editor’s note: The SEC filing URLs cited in this article follow standard EDGAR document paths for Freshworks (CIK 1544522) and Cloudflare (CIK 1477333). Readers should verify that the links resolve correctly; if the SEC has reorganized its archive or the filing identifiers differ from those listed here, the documents can be located by searching each company’s CIK number directly on EDGAR.
The two filings land against a grim backdrop. According to Layoffs.fyi, the widely cited tracker that aggregates publicly reported tech layoffs, roughly 92,000 workers in the sector have lost their jobs so far in 2026. Close to half of those layoff announcements list AI as the primary reason for the reductions. Critically, that “close to half” figure counts discrete layoff events, not individual workers. Cloudflare-type cases, where the company describes an “operating-model shift” without naming AI, are not included in that tally; only announcements that explicitly cite AI are counted. That year-to-date total already surpasses the startup downsizing wave that followed the onset of the pandemic in early 2020, when venture-backed firms slashed payrolls as revenue projections collapsed almost overnight.
What the SEC filings actually say
Freshworks left little room for interpretation. Its filing explicitly connects the restructuring to a technology-driven overhaul, framing the cuts not as a response to slowing sales but as a bet that AI and automation can absorb work currently done by employees. The company did not disclose exactly how many positions would be eliminated, but the language points to a permanent reorganization rather than a temporary hiring freeze.
Cloudflare’s filing is less direct. The San Francisco-based internet-infrastructure company described its plan as a shift in operating model, a phrase broad enough to cover automation, outsourcing, or straightforward cost discipline. In an environment where nearly every major tech firm is pouring capital into AI infrastructure, analysts widely read “operating-model shift” as shorthand for automation-driven change. But Cloudflare did not spell that out, which means classifying its cuts as “AI-driven” requires an inference the company itself has not made on the record. For the purposes of the headline claim that close to half of layoff announcements cite AI, Cloudflare’s cuts fall outside that count precisely because the company did not use the term.
That distinction matters more than it might seem. It illustrates a problem running through the entire 2026 layoff narrative: the line between “AI-driven” and “AI-adjacent” is blurry, and no standardized definition exists for separating the two. The Bureau of Labor Statistics does not yet track AI as a cause in its mass-layoff statistics or its Job Openings and Labor Turnover Survey data, leaving journalists and analysts to rely on company statements that vary wildly in specificity.
How reliable is the 92,000 figure?
Layoffs.fyi has earned credibility through years of consistent tracking. Major outlets, including Bloomberg, The Wall Street Journal, and TechCrunch, have cited its data to contextualize previous waves of tech job losses. The tracker compiles publicly reported layoff events and categorizes them by the reason each company provides, whether in press releases, internal memos that become public, or regulatory filings.
But it is not a government dataset, and its totals carry real limitations. The count depends on what companies choose to disclose. Smaller firms that quietly reduce staff without a press announcement may never appear. Conversely, some companies may play up AI’s role in their messaging to frame cuts as strategic and forward-looking rather than reactive, inflating the share attributed to automation.
No independent federal source currently confirms either the 92,000 total or the proportion linked to AI. An important clarification: the “close to half” figure refers to the share of layoff announcements citing AI, not necessarily half of all individual workers affected. A single large company cutting thousands without mentioning AI could significantly shift the per-worker ratio.
The safest way to treat the tracker’s numbers is as directional indicators: strong enough to establish that a significant wave of AI-linked restructuring is underway, but not precise enough to serve as a final count. They are most useful when paired with primary documents like the Freshworks and Cloudflare filings, which provide the kind of legally binding specificity that aggregated data cannot.
What the numbers leave out
Absent from nearly all of the available data is any picture of what happens to the people behind the numbers. Neither Cloudflare nor Freshworks disclosed details about reskilling programs, internal transfers, or severance terms beyond the estimated restructuring charges. Layoffs.fyi tracks events, not outcomes.
No major institutional research firm, whether Challenger, Gray & Christmas, Gartner, or McKinsey, has yet published a comprehensive study quantifying AI’s specific share of 2026 job losses or tracking where displaced workers end up. Nor has any named economist or labor analyst gone on the record with a definitive assessment of AI’s net impact on 2026 employment, a silence that itself underscores how early this shift remains. That gap leaves several urgent questions unanswered:
- Which job categories are most exposed? Customer support, content moderation, and junior software-engineering roles have been flagged anecdotally, but hard data on role-level displacement remains scarce.
- Are the same companies eliminating positions in one department while hiring AI specialists in another, partially offsetting the net loss?
- Are laid-off workers finding comparable roles elsewhere in tech, or are they leaving the sector entirely?
- Are industries outside technology, such as financial services, media, or business-process outsourcing, experiencing a parallel wave of AI-linked cuts? Anecdotal reports suggest they are, but no centralized tracker equivalent to Layoffs.fyi covers those sectors with the same rigor, making cross-industry comparison difficult.
Unemployment-claims data from state workforce agencies could eventually help fill in the picture, but those figures lag by weeks or months and do not break out causes at the granularity needed to isolate AI-related separations. Meanwhile, the federal government has not signaled any near-term plan to add AI as a tracked cause in Department of Labor reporting, leaving a significant blind spot in the public record.
When AI is the reason and when it is the excuse
For workers scanning headlines about the latest round of cuts, the most pressing question is not whether AI is reshaping tech payrolls. The Freshworks filing settles that much. The harder question is how often AI serves as a genuine driver of restructuring versus a convenient narrative that lends a veneer of strategic vision to cuts that would have happened anyway, whether because of slowing growth, elevated interest rates, or the simple reality that many companies over-hired during the boom years of 2021 and 2022.
The current evidence offers only a partial answer. Corporate disclosures confirm that AI is shaping some layoff decisions at the company level. Aggregate trackers suggest the pattern is widespread. But the documentation thins out fast beyond those two layers. There is almost no visibility into reskilling pipelines, long-term career outcomes, or the net effect on employment once AI-related hiring is factored in.
Why the documentation gap matters more than the headline number
What is clear, as of late May 2026, is that the shift is no longer speculative. AI has moved from background factor to explicit rationale in regulated filings, and the pace of disclosed restructurings shows no sign of slowing. The documentation at the company level is strong. The aggregate data is patchy. And for the tens of thousands of workers whose jobs have already disappeared, the question that matters most, where they go from here, is the one nobody is tracking at all.
David M. Keller is a finance writer based in Columbus, Ohio, covering personal finance and consumer-focused economic topics. He earned his degree in journalism from Ohio University and began his career reporting on local business and economic trends for a regional media outlet. Since then, he has contributed to a variety of online publications, focusing on clear, practical coverage of topics such as cost of living, debt, and everyday financial decision-making.
