How we count.

jobloss.ai records AI-linked layoffs of US workers only. A German bank cutting a thousand jobs because of AI does not appear on this dashboard. The Alliance for Secure AI maintains this as a domestic public-interest dataset, and the scope is deliberate.

That decision is not a claim that most AI-linked layoffs happen in the United States. It is a claim about what can be counted credibly. American workforce reductions are uniquely traceable: the WARN Act, securities filings, and an active business press mean that US job cuts are reported with company names, headcounts, and dates. In much of Europe, comparable events surface only after works council consultations, and in some jurisdictions never surface publicly at all. A global tracker built with our methods would still over-index on the United States — not because more Americans are losing work to AI, but because American losses are easier to count.

For the same reason, this data should not be used to compare countries. Cross-country figures don't yet exist at consistent fidelity, and differences in labor law and reporting practice make casual comparisons misleading.

A report enters the ledger when it meets three criteria:

• At least 100 US jobs eliminated in a single announcement, across any sector. Smaller actions are excluded for signal-to-noise.
• AI is a material factor in the company's stated reason. Language like “efficiency,” “restructuring,” “productivity,” or “automation” qualifies — we don't require an executive to say “we replaced a team with AI.” This is a moderate standard, deliberately: it captures the broad pattern of AI-justified workforce reductions while excluding clearly unrelated cuts.
• First-time announcement. Restated totals, duplicate filings covering events already in the ledger, hiring freezes that did not reduce headcount, and cuts attributed entirely to non-AI factors are excluded.

Every report carries one of three attribution tags. The tag reflects the strength of the AI causal link, not the size of the layoff.

We draw from a mix of public sources, weighted toward primary disclosures where they exist:

• Regulatory and securities filings — SEC reports, WARN Act notices, and equivalent state filings.
• Mainstream business press — AP, Reuters, Bloomberg, the Wall Street Journal, the Financial Times, and CNBC.
• Trade publications covering specific verticals — technology, financial services, retail, logistics, healthcare.
• Local news, particularly for actions concentrated in specific metropolitan areas.

Every figure on this site links to its originating source. Where multiple sources cover the same event, we prefer primary disclosures and the earliest credible reporting.

We correct in public. If a figure changes after we publish — because the company revises its disclosure, the reporting source updates, or we made an error — we log the change in the update log with the date and the reason, and surface a banner on the homepage when the correction is material.

Spotted something wrong? jobloss@secureainow.org.

The Alliance for Secure AI, AI Job Loss Tracker. Available at jobloss.ai.