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TL;DR
A Goldman Sachs 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. Goldman’s public research on earlier technology-related layoffs finds lasting wage and employment costs, but the new AI estimates are preliminary and the note is not public.
Workers likely displaced by AI since 2025 have taken about a 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, according to a Goldman Sachs note reported by Fortune. The findings suggest that early AI-related layoffs may resemble earlier technology-driven job losses, which Goldman’s historical research links to prolonged employment and wage costs.
The note, written by Goldman economist Pierfrancesco Mei and dated October 29, is not publicly available. The figures for workers affected since 2025 come from Fortune’s account of the note, which quoted it; they have not been independently confirmed from the underlying document. Goldman’s analysis estimates which workers were likely displaced by AI because government surveys do not ask whether AI caused a job loss.
As described in Fortune’s report, Goldman used Labor Department data on displaced workers, examining more than 15,000 people who lost jobs between 2016 and 2025. It combined occupational exposure to AI, the pace of AI adoption in each industry and whether a position was eliminated into a score. Workers in the top 30% were classified as “likely AI-displaced.” Goldman found no significant employment-outcome gap between that group and other laid-off workers for job losses before 2023, according to the report.
The note reportedly found that workers aged 35 and older took about five weeks longer than comparable laid-off workers to return to full-time work; workers under 35 took about three weeks longer. Those classified as AI-displaced were also more likely to leave their former occupation and industry. Yet some who found new work, particularly older workers, moved into roles with similar or higher AI exposure, Fortune reported.
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 Costs Continue After Layoffs
The findings shift attention from the number of job cuts to what follows: how long workers search, what they earn when rehired, and whether new employment lasts. A longer period without work can carry costs beyond the initial loss of income, while a move into another AI-exposed role may leave a worker facing further change. The note’s reported results are early estimates, not a complete measure of AI’s effect on employment.
Goldman’s public historical analysis gives the comparison more weight, while not proving that AI will produce identical outcomes. In that research, workers displaced by technology took about one month longer to find work and earned more than 3% less in real terms when rehired than workers laid off from stable or growing occupations. Over the following decade, their real earnings growth was nearly 10 percentage points lower. The gap suggests that the economic effect of technological change can persist after a worker has secured another job.
The age findings also matter for employers and policymakers weighing support after layoffs. Separate Labor Department figures cited in the source material show a marked age gap among long-tenured workers: by January 2026, 72.9% of those aged 25 to 54 were working again, compared with 57.3% of those aged 55 to 64. Those figures cover laid-off workers generally, not a confirmed AI-displaced group, so they provide context rather than direct evidence about AI.
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Four Decades of Displacement Data
Goldman’s comparison draws on publicly available research published in its June 2026 “Top of Mind” report and a September summary. Mei and colleagues Jessica Rindels and David Mericle examined more than 300 occupations across several decades, identifying jobs exposed to technological change and following workers through the National Longitudinal Surveys, which have tracked more than 20,000 people over their careers.
That historical research reports that displaced workers who found new jobs lost more than 3% in real pay, while workers laid off from stable or growing occupations had negligible losses. Over the next decade, the technology-displaced group’s real earnings grew nearly 10 percentage points less. Goldman also found that workers who retrained within three years had about two percentage points more real wage growth over ten years and a roughly 10-point lower chance of becoming unemployed again. These are historical associations, not a guarantee that retraining will produce the same results for people affected by AI today.
The current estimate uses a different, indirect method because official surveys do not identify AI as the cause of a layoff. Its classification combines exposure, industry adoption and job elimination; it does not establish that AI alone caused any individual worker’s job loss. Goldman reportedly used the absence of a significant pre-2023 outcome gap as a check on its approach, but the analysis remains an estimate.
““comparable in magnitude””
— Pierfrancesco Mei, Goldman Sachs economist, as quoted in Fortune
Early AI Estimates Have Limits
The Goldman note is not public, and its reported findings are available through Fortune’s account, rather than direct examination of the full analysis. The figures should be treated as reported estimates, not independently verified results. The source material says other coverage repeated Fortune’s numbers; it does not provide separate access to the note.
Goldman’s method identifies workers who are more likely to have been affected by AI based on occupation, industry and job elimination. It cannot establish that AI caused each layoff. The analysis also covers a short period: the note reportedly assessed job losses since 2025, and Goldman said it was too early to assess effects across education, region and other dimensions. The available information does not show how the results vary across those groups or whether the employment gap will persist.
It is also unclear how much of the reported difference reflects AI adoption specifically, broader labor-market conditions or characteristics of the workers and industries involved. Goldman’s historical findings describe earlier technological changes, but they cannot by themselves predict the size or duration of future AI-related effects.
More Evidence Will Shape the Picture
The next useful evidence will be longer-term follow-up showing whether workers classified as likely AI-displaced return to work, what their replacement jobs pay and whether they remain employed. Further analysis by age, education, region and industry could clarify who faces the largest barriers, but Goldman’s reported note does not yet settle those questions.
Readers should also distinguish future reported estimates from official counts. Because government surveys do not directly ask whether AI caused a job loss, assessments will continue to depend on indirect measures unless those surveys change. No next release date for a public version of the October note is specified in the source material. For now, Goldman’s historical research offers a longer view, while the AI-specific findings remain preliminary.
Key Questions
What did Goldman Sachs find about workers likely displaced by AI?
According to Fortune’s report of a Goldman Sachs note, workers likely displaced since 2025 took about one month longer to find new work than other laid-off workers and were roughly 10 percentage points more likely to remain unemployed a year later.
Are the AI-displacement figures confirmed by government data?
No. Government surveys do not ask whether AI caused a worker’s job loss. Goldman reportedly estimated likely displacement using occupational AI exposure, industry adoption and whether a position was eliminated. The note itself is not public, and its figures are reported through Fortune.
What does Goldman’s historical research say about technology layoffs?
Goldman’s public research says workers displaced by earlier technologies took about a 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 following decade than a comparison group.
Did the analysis find that older workers faced a longer return to work?
Yes, in the AI-related estimates reported by Fortune: workers aged 35 and older took about five weeks longer to return to full-time work, compared with about three weeks longer for those under 35. These are reported estimates, not a direct government count of AI-caused layoffs.
What remains unknown about AI-related layoffs?
The available evidence does not establish that AI caused each job loss, how the effects differ by education or region, or whether the reported employment and wage gaps will continue. Goldman said it was too early to assess several of those dimensions.
Source: ThorstenMeyerAI.com
