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TL;DR
A Goldman Sachs client note, reported by Fortune, says workers likely displaced by AI since 2025 took about a month longer to find work than other laid-off workers and were more likely to remain unemployed a year later. The estimates are preliminary and rely on an indirect measure of AI-related job loss; Goldman’s public historical research finds that earlier technology displacement was linked to lasting wage and earnings losses.
A Goldman Sachs analysis reported by Fortune says workers likely displaced by AI since 2025 took about one month longer to find new jobs than other laid-off workers and were roughly 10 percentage points more likely to remain unemployed a year later. The findings suggest that early AI-related job losses may follow a pattern seen in earlier technology shocks, when displacement was associated with prolonged job searches and weaker earnings—but Goldman’s new estimates are preliminary and based on an indirect measure of AI-related layoffs.
The estimates come from a Goldman client note dated October 29, written by economist Pierfrancesco Mei. Goldman’s note is not public; the figures were reported by Fortune the following day, based on its account of the note. They should be treated as reported findings, not independently verified results. The source material says other coverage repeated Fortune’s figures rather than independently examining the note.
Because government surveys do not ask whether AI caused someone to lose a job, Goldman constructed a measure using Labor Department data on displaced workers. It examined more than 15,000 people who lost jobs between 2016 and 2025, combining occupational exposure to AI, the pace of AI adoption in the industry and whether a position was eliminated. Workers in the top 30% of its score were classified as “likely AI-displaced.” Goldman reportedly found no significant difference between that group and other laid-off workers for job losses before 2023, when AI adoption began to rise.
For losses since 2025, the reported note found that likely AI-displaced workers faced a longer search and were more likely to remain out of work. Workers aged 35 and older took about five weeks longer than comparable laid-off workers to return to full-time work; those under 35 took about three weeks longer. The group was also more likely to leave its previous occupation or industry. Among those rehired, however, some—particularly older workers—returned to jobs with similar or higher AI exposure, according to Fortune’s account.
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 jobs cut to what happens after workers lose them. A longer job search can mean more time without wages, while returning to work in a different occupation or industry may require a change in skills, location or career path. The reported one-year unemployment gap suggests that the effects may persist well beyond the initial separation for some workers.
Goldman’s public research on earlier technological displacement adds a longer-term warning, though it does not establish that AI will produce identical outcomes. In that historical analysis, displaced workers took about one month longer to find work, lost more than 3% in real pay when rehired, and had nearly 10 percentage points less real earnings growth over the next decade than workers who had not been laid off. Those figures make the current estimates consequential for workers, employers and policymakers, but they are evidence about past technology shocks—not a forecast of the precise scale of AI’s effects.
Age is another concern. Government data cited in the source material show that by January 2026, 72.9% of long-tenured workers aged 25 to 54 were working again, compared with 57.3% of those aged 55 to 64. Those figures cover long-tenured displaced workers generally, not specifically people laid off because of AI. They nevertheless point to a broader reemployment gap that could shape how AI-related disruption affects different age groups.
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Four Decades of Technology Displacement
Goldman’s comparison draws on research its economists published publicly in a June 2026 “Top of Mind” report and a September summary. Mei, Jessica Rindels and David Mericle studied workers across more than 300 occupations, identifying jobs with greater exposure to technological change in each decade since the 1980s. They followed employment and earnings using National Longitudinal Surveys that have tracked more than 20,000 workers over their careers.
That historical work found that workers displaced from technology-exposed occupations took longer to regain employment and experienced weaker pay outcomes than workers laid off from stable or growing occupations. It also examined retraining: workers displaced by technology who retrained within three years had about two percentage points more real wage growth over the following decade and a roughly 10-point lower chance of becoming unemployed again. These are historical associations reported by Goldman; they do not establish that retraining alone caused the improved outcomes.
The source material also cites Bureau of Labor Statistics data showing a change in reemployment pay among long-tenured workers who returned to full-time jobs. About 49% earned as much as before or more, down from about 62% two years earlier. This is a measure for the broader group of long-tenured displaced workers, not an AI-specific result.
““Comparable in magnitude””
— Pierfrancesco Mei, Goldman Sachs economist, as quoted in Fortune
How Much Can Early Data Tell Us?
The central uncertainty is whether a worker’s job loss was actually caused by AI. Goldman’s score combines exposure, industry adoption and job elimination, but it is an estimate rather than a direct report from workers or employers. A job in an AI-exposed occupation may disappear for other reasons, while AI-related changes may affect work without eliminating a position. The method therefore identifies workers considered likely to have been displaced, not confirmed cases.
The new note is also unavailable for public review in the source material. The post-2025 figures come through Fortune’s reporting, and it is not clear from the supplied information how large the relevant subgroup was or how precise the estimates are. Goldman itself reportedly cautioned that it is too early to assess outcomes across education and geography. The findings do not establish how many jobs AI has eliminated overall, how much of the reemployment gap AI caused, or whether the same pattern will continue as adoption changes.
Goldman also expects job losses linked to AI to accelerate if economic growth slows, based on its analysis that displacement costs are larger during downturns. That is an economic expectation, not a confirmed outcome. The timing and scale of any future acceleration remain uncertain.
Tracking Reemployment and Earnings
The next evidence will come from following displaced workers beyond the initial job search: whether they return to full-time work, how long they remain unemployed, what they earn, and whether they move into jobs with different exposure to AI. Future labor-market data and updated research may clarify whether the gaps reported for losses since 2025 persist across age groups, regions and levels of education.
Goldman’s public historical work points to retraining as one factor associated with stronger longer-term outcomes, but the reported findings do not establish which programs work best or whether those results will carry over to AI-related displacement. For now, the clearest conclusion is limited: the early estimates resemble past technology shocks on some measures, while the scale, causes and lasting effects of AI-related job loss remain unresolved.
Key Questions
What did Goldman Sachs find about workers likely displaced by AI?
According to Fortune’s report on a Goldman client note, workers classified as likely AI-displaced after 2025 took about one 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 these confirmed AI-related layoffs?
No. Goldman used an indirect score based on occupational AI exposure, industry adoption and whether a position was eliminated. It identifies workers considered likely AI-displaced; it does not confirm that AI caused each job loss.
What does the historical research say about technology layoffs?
Goldman’s public research found that workers displaced by earlier technology changes took longer to find work and had weaker pay and earnings growth than workers who had not been laid off. Those historical results are not a precise forecast of AI’s future effects.
Which workers appear to face longer reemployment delays?
In the reported Goldman note, workers aged 35 and older took about five weeks longer to return to full-time work than comparable laid-off workers; those under 35 took about three weeks longer. The figures are reported estimates, not a complete measure of every worker’s outcome.
Could a recession worsen AI-related job losses?
Goldman’s economists expect AI-related job losses to speed up if the economy slows, and the firm’s historical analysis finds displacement costs are larger in downturns. That is an expectation, not a confirmed forecast of when or how many additional jobs would be affected.
Source: ThorstenMeyerAI.com
