27JUL

New York moves to count AI job losses

3 min read

10:02UTC

The New York State Assembly passed A 9581 on 3 June, requiring the state Labor Department to report annually on how AI affects hiring, and sent it to the Senate.

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Key takeaway

New York's Assembly voted to make the state count AI's effect on hiring each year.

The New York State Assembly passed bill A 9581 on Wednesday 3 June 2026, requiring the state Labor Department to publish an annual report on artificial intelligence's effect on hiring and employment ¹. The bill cleared the Assembly and went to the Senate for consideration. It is a measurement mandate rather than a restriction: the state would have to count what AI is doing to jobs, a number no federal instrument currently produces.

The gap A 9581 targets is real. No US federal agency currently measures how many jobs AI removes, which leaves legislators arguing over displacement without an agreed figure. New York's earlier WARN-style disclosure law showed the difficulty: in its first year, 162 companies covering 28,300 workers attributed none of their cuts to AI, because firms decide what reason to state.

The move runs against the opposite direction taken elsewhere. Colorado moved the opposite way in May, replacing its AI Act with a weaker notice-only regime that stripped out the substantive obligations. Two states, two contrary instincts on the same question, with no federal floor to reconcile them. A 9581's value depends on whether the Senate passes it and whether annual reporting can capture a channel that runs mainly through hires never made, the part of displacement that leaves no filing behind.

Deep Analysis

In plain English

The New York State Assembly, the lower house of the state's legislature, passed a bill on 3 June 2026 requiring the state's Department of Labor to publish an annual report on how artificial intelligence is affecting hiring in New York. The bill now moves to the Senate. No US government agency currently produces a regular, official count of how many jobs have been affected by AI. This bill would require New York's Labour Department to start building that record. This bill would require New York's equivalent of the UK's ONS to start keeping that record. Critics point out that a report with no penalties attached and no specific comparison metric may not change employer behaviour. But supporters argue that making the data official and public is the first step toward stronger legislation.

What could happen next?

Precedent
If the New York Senate passes A 9581, it becomes the first US state to create a statutory annual AI-hiring-impact measurement obligation, potentially establishing a template other states adopt.

Source Landscape

This story draws on neutral-leaning sources

Primary parallel: The UK's Disclosure and Transparency Rules introduced in 2006 required listed companies to report executive remuneration in standardised form.

A 2016 review by the High Pay Centre found the reports generated voluminous data but minimal behavioural change until the 2019 gender pay gap reporting requirement added a specific comparison metric and a named publication deadline that created social pressure alongside legal obligation. A 9581's annual report without a comparison metric or mandatory publication deadline follows the pre-2019 UK template rather than the more effective post-2019 one.

Counter-parallel: California's 2002 SB 1 mandatory pay equity reporting requirement was similarly weak on enforcement at passage and was later strengthened by SB 1162 in 2022. The pattern suggests passage of a weak reporting bill is the legislative prerequisite for the stronger enforcement legislation that follows once the data makes the problem visible. A 9581 may be structurally positioned as Phase 1.

Consensus view: The Brennan Center for Justice and Georgetown Law's workplace technology project both describe A 9581's annual-reporting requirement as the minimum viable regulatory response: it generates a factual record without imposing a compliance burden that would trigger industry challenge. The Hawley-Warner federal letter to agencies pursued the same logic at the federal level, and both efforts share the assumption that measurement precedes action.

Counter-view: Cornell ILR School's Alexander Colvin argues mandatory annual reporting without a disclosure trigger date or penalty provision converts the requirement into a box-ticking exercise. New York's prior 2023 AI hiring bias law (Local Law 144) generated extensive reporting but produced almost no enforcement actions, because the reporting requirement did not create a private right of action for affected workers.

The pattern from Local Law 144 is instructive: after nearly a year of operation, zero of 162 mass layoff notices in New York cited AI or automation under the updated WARN Act , indicating firms report what the law technically requires, not what it intends to surface.

Key tension: Whether the annual Labour Department report generates politically actionable data or becomes a statistical annex that legislators cite but cannot act on because the reporting cadence is too slow to match quarterly restructuring cycles.

Sources:Transparency Coalition

Mentions:New York State →California →WARN Act →Brennan Center for Justice →New York A 9581 →

First Reported In

Update #12 · Jobs report says fine, layoff report says no

Transparency Coalition· 8 Jun 2026

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Causes and effects

Caused by

Colorado guts its AI hiring law

Colorado gutting its AI Act to notice-only sharpens the regulatory divergence that California SB 951's 90-day trigger represents.

Occurred 16 May 2026

Read story →

This Event

New York moves to count AI job losses

It is a bid to build the AI-employment data Congress and the federal statistical agencies have not produced.

Led to

States write the AI law Congress won't

New York Assembly passed A9581 alone on 3 June; Senate passage is the new development that advances the bill to Hochul.

Occurred 10 Jun 2026

Read story →

Different Perspectives

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

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 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 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 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

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.