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TL;DR
Goldman Sachs estimates that workers likely displaced by AI since 2025 have taken about a month longer to find work than other laid-off workers and were roughly 10 percentage points more likely to remain unemployed a year later. The figures come from a client note reported by Fortune, not a publicly available Goldman document; the bank says the pattern resembles earlier technology-driven job losses, whose effects often lasted for years.
Workers likely displaced by AI since 2025 are taking about a month longer to find new jobs than other laid-off workers and are roughly 10 percentage points more likely to remain unemployed a year later, according to a Goldman Sachs client note reported by Fortune. The bank’s analysis says their early experience resembles past technology-driven job losses, which were associated with lasting employment and pay setbacks.
Goldman’s note, dated October 29, is not publicly available. Fortune reported its findings on October 30, quoting the research by economist Pierfrancesco Mei. The figures on recent AI-related displacement should therefore be treated as reported findings, not as numbers independently verified from the note itself.
Because government surveys do not ask workers whether AI caused their job loss, Goldman constructed an estimate using Labor Department data on displaced workers. Fortune reported that the analysis covered more than 15,000 people who lost jobs between 2016 and 2025, scoring their occupations’ AI exposure, industry adoption and whether the job itself was eliminated. Workers in the top 30% of that score were classified as “likely AI-displaced.” Goldman found no significant difference from other laid-off workers for job losses before 2023, Fortune said.
For job losses since 2025, Fortune reported that the likely AI-displaced group took about one month longer to find work and was roughly 10 percentage points more likely to still be unemployed one year later. Workers aged 35 and older reportedly took about five weeks longer than comparable laid-off workers to return to full-time work, while those under 35 took about three weeks longer. The report also said displaced workers were more likely to leave their previous occupation or industry, though some who found jobs moved into roles with similar or higher AI exposure.
Infographic 01 · What happens after the pink slip
The first AI layoffs look like 40 years of tech layoffs
A longer search, a smaller paycheck and slower growth for years. Goldman’s new estimate for AI-exposed workers lines up with its long-run history.
The first AI wave, since 2025
Likely AI-displaced vs. other laid-off workers, US. Note not public; figures as reported by Fortune.
Forty years of tech shocks
Workers displaced from technology-disrupted occupations, US.
“Comparable in magnitude” to earlier waves of technological change, whose damage was “long-lasting.”Goldman Sachs economist Pierfrancesco Mei, as quoted by Fortune
How Goldman spots “AI-displaced” workers: no survey asks about AI, so it scores each job loss by the occupation’s AI exposure, the industry’s AI adoption and whether the position was eliminated, and treats the top 30% as likely AI-displaced (more than 15,000 workers, 2016–2025). An estimate, not a count.
Sources: Fortune, 30 Oct 2026 (reporting the Goldman note of 29 Oct 2026) · Goldman Sachs, Top of Mind #149, 25 Jun 2026, p. 15 · Goldman Sachs Insights, 11 Sep 2026. pp = percentage points.
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The Cost Extends Beyond Layoff Day
The findings shift attention from the number of announced cuts to what happens afterward: how long workers remain out of work, what they earn when rehired and whether they can stay in the new job. Goldman’s historical research suggests that a faster return to employment does not necessarily mean workers have recovered financially.
In research published publicly in 2026, Goldman economists examined technology-related displacement over several decades. The bank’s findings, as summarized in the supplied source, say affected workers took about a month longer to find work, lost more than 3% in real pay on reemployment and had nearly 10 percentage points less real earnings growth over the following decade than workers who had not been laid off. Those historical results provide a comparison, not proof that today’s AI-displaced workers will experience identical outcomes.
The age differences could matter for workers making plans after a job loss and for employers deciding how to support them. The source also reports that, in Goldman’s historical data, workers displaced by technology who retrained within three years had about 2 percentage points more real wage growth over a decade and a roughly 10-point lower chance of becoming unemployed again. These are associations in the analysis; the material does not establish that retraining alone caused the better outcomes.
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How Goldman Built Its Comparison
The new estimate draws on the Labor Department’s Displaced Worker Supplement to the Current Population Survey, rather than a direct survey asking whether AI caused a particular layoff. Goldman combined measures of occupational exposure to AI, the pace of AI adoption in an industry and whether a position was eliminated. Its “likely AI-displaced” label is therefore an analytical classification, not a confirmed reason for each individual job loss.
Goldman’s historical comparison comes from its publicly released research. A June 2026 “Top of Mind” report and a September summary by Mei and colleagues Jessica Rindels and David Mericle tracked workers across more than 300 occupations, drawing on National Longitudinal Surveys that have followed over 20,000 people through their careers. The work compared workers in occupations exposed to technological change with workers in stable or growing fields.
The timing matters: Goldman’s reported recent findings cover job losses since 2025, while its historical research spans decades and different technologies and economic conditions. The similarity Goldman identifies is a pattern in reemployment and earnings, not a claim that AI’s effects will match every earlier wave.
““comparable in magnitude””
— Pierfrancesco Mei, Goldman Sachs economist, as quoted in Fortune
Limits of the Early AI Estimates
The Goldman note is a client document and is not public; the recent figures here come from Fortune’s reporting, as described in the supplied source. The source says other coverage repeated Fortune’s numbers, so those reports do not amount to independent confirmation of the underlying analysis.
The classification also involves uncertainty. The government survey does not establish that AI caused a given job loss, and Goldman’s score combines exposure, industry adoption and job elimination to identify workers considered likely to have been displaced by AI. The reported results should not be read as a definitive count of AI-caused layoffs or as proof that AI was the reason for every worker’s departure.
Goldman said it was too early to assess outcomes across all dimensions, including education and region. The supplied material does not provide the full note, detailed methodology or sample sizes for each reported subgroup. It also does not establish whether the recent differences will persist as more data become available, or how much of the observed job-search gap is attributable to AI rather than other conditions.
More Data Will Test the Pattern
The next test will be whether subsequent labor-market data show that the longer job searches and unemployment gap persist as more workers experience displacement. Goldman’s framework relies on labor surveys and an estimated AI-displacement category, so further observations may sharpen or change the picture, especially for groups the bank said it could not yet assess fully.
Economic conditions are another factor. The source says Goldman’s historical research found displacement costs were larger during downturns, and that its economists expect AI-related job losses to accelerate if the economy slows. That is a forecast, not a confirmed outcome. Any assessment of future losses will need to distinguish AI-related displacement from job cuts driven by broader economic weakness.
For now, the clearest conclusion is limited: Goldman’s reported early estimates point to a difficult return to work for some people classified as likely AI-displaced, while its historical research shows that technology-related job loss can carry consequences beyond the initial layoff. The scale, duration and distribution of the AI-era effects remain unsettled.
Key Questions
What did Goldman Sachs find about workers likely displaced by AI?
According to Fortune’s report of a Goldman client note, workers classified as likely AI-displaced since 2025 took about a month longer to find work than other laid-off workers and were roughly 10 percentage points more likely to remain unemployed a year later.
Are the reported figures publicly confirmed by Goldman?
The note is not public. The recent figures are reported by Fortune, which quoted the note; readers cannot independently check the full document from the information provided.
How did Goldman identify likely AI-related job losses?
Goldman reportedly combined a job’s AI exposure, the rate of AI adoption in its industry and whether the position was eliminated, using Labor Department displaced-worker data. The label is an estimate, not a government finding that AI caused a specific layoff.
What did Goldman’s historical research say about technology layoffs?
Goldman’s public research says workers displaced by technology historically took longer to find new jobs, experienced real-pay losses on reemployment and had weaker real earnings growth over the next decade than workers who were not laid off. Those findings offer context but do not establish that AI-related outcomes will be identical.
What remains unknown about AI-related layoffs?
The full client note and detailed methodology are not available in the supplied material. Goldman also said it is too early to assess differences by education and region, and the reported estimates do not prove that AI caused each job loss in the group.
Source: ThorstenMeyerAI.com
