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AI: Jobs, Power & Money
27JUL

NY AI layoff law: 162 filings, zero hits

2 min read
10:02UTC

New York required companies to disclose AI's role in mass layoffs. After a year, 162 companies covering 28,300 workers attributed zero cuts to AI.

EconomicAssessed
Key takeaway

Zero of 162 companies disclosed AI as a factor in layoffs despite a legal obligation to do so.

In 2025, New York State updated its Worker Adjustment and Retraining Notification Act to require companies to disclose AI's role in mass layoffs, becoming the first US jurisdiction to mandate such reporting. After nearly a year of operation, the results are in. 1 Zero of 162 companies filing layoff notices attributed cuts to AI or technological automation. Those filings covered more than 28,300 workers, including staff at Amazon and Goldman Sachs.

Non-compliance currently carries a penalty of $500 per day. Proposed legislation would raise that to $10,000 per violation and strip companies of state grants and tax incentives for five years. That tougher bill has not advanced.

Silence on this scale is evidence, not absence. Harvard Business Review reported that only 2% of layoffs followed actual AI deployment . Oxford Economics called AI's layoff role "overstated" . Both relied on corporate claims taken at face value. New York's data shows those claims are legally shielded as well as reputationally incentivised. Companies that cut 28,300 jobs had the opportunity and the obligation to say whether AI played a role. Every one said no. Either AI genuinely drives none of the displacement in the nation's financial capital, or the disclosure framework is failing.

Deep Analysis

In plain English

New York passed a law requiring companies to say whether AI played a role when they do mass layoffs. After nearly a year, 162 companies laid off more than 28,000 people, including workers at Amazon and Goldman Sachs. Not one company said AI was involved. The penalty for lying or not disclosing is $500 a day. For billion-dollar companies, that is a trivial fine. Until the penalty is meaningful, there is no incentive to tell the truth.

Deep Analysis
Root Causes

The $500/day penalty is structurally inadequate. For a company like Amazon or Goldman Sachs, potential exposure of $500 per day during a WARN period is a rounding error against litigation risk or reputational exposure from admitting AI-driven displacement. The incentive structure rewards non-disclosure.

Legal uncertainty also suppresses attribution. The definition of AI-driven job loss has not been tested in court. Companies face asymmetric risk: disclosing AI as a reason invites class actions and union bargaining claims, while non-disclosure carries only a civil penalty. Rational legal counsel will advise against attribution until the definition is litigated.

What could happen next?
  • Consequence

    The New York result will be cited in Congressional debates as evidence that voluntary disclosure frameworks cannot generate honest AI attribution data, strengthening the case for mandatory federal reporting with meaningful penalties.

    Short term · High
  • Risk

    Other states considering WARN Act amendments may model weak penalty structures on New York, producing the same zero-attribution outcome and wasting a decade of potential evidence collection.

    Medium term · Medium
  • Precedent

    New York's failure is the most important data point in the AI disclosure debate: it proves empirically that disclosure laws without credible enforcement produce no data.

    Long term · High
First Reported In

Update #3 · The AI jobs data contradicts itself

Bloomberg Law· 28 Mar 2026
Read original
Different Perspectives
European Commission
European Commission
The European Commission's draft Annex III guidelines, closed for comment on 23 July, treat algorithmic scoring in recruitment, pay and termination as high-risk regardless of whether a human signs off, echoing Spain's Audiencia Nacional ruling 101/2026 on concealed scheduling algorithms. Brussels is shifting the fight from counting AI job losses to assigning legal liability for the tools themselves.
Office for National Statistics
Office for National Statistics
The Office for National Statistics recorded UK vacancies rising to 712,000 on 21 July, the first quarterly increase this beat has tracked, with payrolled employment down 85,000 on the year against May's 210,000 fall. The bulletin names no AI cause anywhere, and that is the point: nothing in the release confirms the displacement story it gets cited to support.
Christian Klein, SAP
Christian Klein, SAP
Christian Klein told investors on 23 July that SAP's research headcount will not grow for twelve months because AI agents and their token costs are absorbing the work, not because SAP is cutting jobs. He frames it as commercial arithmetic: the cost of AI-assisted coding tokens plus the salaries specialist AI hires command, not people being replaced by machines.
Betsey Stevenson, University of Michigan
Betsey Stevenson, University of Michigan
Betsey Stevenson argued that the 187,000 jobless-claims reading describes a market that hires little and fires little, not one AI is emptying. She said the real damage hides in eligibility rules and suppressed job postings, not in the headline layoff counts employers keep denying.
Comisiones Obreras, UGT and Concentrix's A Coruña works committee
Comisiones Obreras, UGT and Concentrix's A Coruña works committee
Comisiones Obreras, UGT and Concentrix's A Coruña works committee blamed Microsoft's push toward AI self-service for the 80 redundancies unions signed off on 22 July, not unavoidable business cause. A second Coruña procedure covering 80 more jobs runs to a 31 August deadline, and the unions want the state, not the employer, setting the pace of AI-driven cuts.
Stanford's 'We Must Act Now' signatories
Stanford's 'We Must Act Now' signatories
More than 200 academics, including 16 Nobel laureates, published a 13 July letter warning of AI-driven labour disruption, citing Daron Acemoglu's NBER estimate that AI's total factor productivity gain stays under 0.66% over ten years. The letter's own cited economics sit well below Goldman Sachs Research's 1.5-percentage-point estimate published the same week.