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TL;DR
A Goldman Sachs client note reported by Fortune says workers classified as likely displaced by AI since 2025 took 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. The estimate is based on job and industry indicators, not a government survey asking whether AI caused a layoff. Goldman’s historical research suggests technology-related job losses can carry lasting pay and employment costs, but the effects of AI remain too early to fully measure.
A Goldman Sachs note dated October 29 estimates that workers likely displaced by artificial intelligence 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 still be unemployed a year later. Fortune reported the findings on October 30; the note is not public, and Goldman’s classification is an estimate rather than a direct count of layoffs caused by AI.
According to Fortune’s account of the note by Goldman economist Pierfrancesco Mei, the analysis examined more than 15,000 people who lost jobs between 2016 and 2025. Because government surveys do not ask whether AI caused a person’s job loss, Goldman used a score combining an occupation’s exposure to AI, the pace of AI adoption in its industry and whether the position was eliminated. People in the top 30% of that score were classified as “likely AI-displaced.” Fortune is the reported source for the new note’s figures; the note itself was not available for independent review.
For workers classified as likely displaced since 2025, Fortune reported a longer return to work and a greater chance of remaining unemployed one year after job loss. The reported age split was also marked: workers aged 35 and older took about five weeks longer than comparable laid-off workers to return to full-time work, while workers under 35 took about three weeks longer. The analysis also found that AI-displaced workers were more likely to leave their previous occupation or industry, though some re-entered work in roles with similar or higher AI exposure.
Goldman’s public historical research offers a comparison, not proof that AI will produce identical outcomes. Its studies of workers displaced by earlier technological change found job searches lasted about a month longer and that reemployed workers lost more than 3% in real pay. Over the following decade, their real earnings grew nearly 10 percentage points less than those of workers who had not been laid off, according to the research described in the source material.
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 Can Follow Workers
The findings shift attention from the number of announced cuts to what happens after a worker loses a job: time out of work, the pay in the next role and whether that role lasts. If the reported pattern continues, an AI-related layoff could have effects that persist beyond the initial separation, especially for older workers and people whose skills or experience do not transfer easily into available jobs.
Historical data cited by Goldman suggest that the impact of technology displacement can extend into later earnings. In that research, 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 than displaced workers who did not retrain. Those are associations in historical data, not a guarantee that training will produce the same result for workers displaced by AI today.
For employers and policymakers, the reported results point to a need to track outcomes after layoffs, not only the number of jobs removed. The source also says Goldman expects displacement costs to be larger in economic downturns. If job cuts increase while hiring slows, workers may face fewer openings at the same time they are searching for new work.
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How Goldman Built the Estimate
The estimate is difficult to make because there is no government survey asking whether AI caused a job loss. Goldman instead used Labor Department data from the Displaced Worker Supplement to the Current Population Survey and combined job-level indicators to identify workers whose former roles were more likely to be affected by AI. The top 30% of its scoring measure were counted as likely displaced, rather than as confirmed cases.
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. That comparison serves as a check on the method, but it does not establish that AI caused each later job loss in the high-scoring group. Other factors could contribute to an employer’s decision to eliminate a role.
The longer historical comparison comes from Goldman research published in June and September 2026. Mei and colleagues Jessica Rindels and David Mericle examined workers in more than 300 occupations, drawing on longitudinal surveys that have followed more than 20,000 people through their careers. That research helps describe earlier technology-related displacement, while the newer AI-linked estimate covers a comparatively short period and relies on a constructed measure.
““comparable in magnitude””
— Pierfrancesco Mei, Goldman Sachs economist, as quoted in Fortune’s report of the client note
AI Attribution Remains Unsettled
The reported figures should be read as estimates, not confirmed counts of AI-caused layoffs. The scoring method identifies workers whose occupations, industries and eliminated positions suggest higher AI exposure, but it cannot establish the cause of an individual employer’s decision. The Goldman client note is not public, so its full methods and caveats cannot be independently checked from the material cited here.
The follow-up period is also short. Job losses since 2025 cannot yet show whether workers will recover their previous earnings, move into lasting employment or face the longer-term outcomes found in historical research. Mei said it was too early to assess effects across dimensions such as education and region. It is also unclear how the results might change as AI adoption, hiring conditions and the wider economy develop.
Longer Follow-Up Will Test the Pattern
The next useful evidence will come from tracking workers over a longer period: how quickly they find stable jobs, what their wages are after inflation, whether they need temporary or additional work, and whether they return to their former industries. Further public reporting or release of Goldman’s methodology could also make it easier to evaluate how the likely-displacement group was defined.
Economic conditions will shape what those results mean. Goldman’s historical research indicates displacement costs are larger during downturns, while the source says its economists expect AI-related job losses to accelerate if the economy slows. That is a forecast, not a confirmed future outcome. For now, the reported early evidence suggests a difficult reemployment path for some workers, while the scale and durability of AI’s effect on jobs remain unsettled.
Key Questions
How many AI-displaced workers did Goldman identify?
The note did not provide a confirmed count of layoffs caused by AI. Goldman used a score based on AI exposure, industry adoption and job elimination, classifying the top 30% as likely AI-displaced.
How much longer did these workers take to find a job?
Fortune reported that workers classified as likely displaced since 2025 took about one month longer to find new work than other laid-off workers. The figure comes from a Goldman client note that is not public.
Were older workers affected differently?
According to Fortune’s report, workers aged 35 and older took about five weeks longer than comparable laid-off workers to return to full-time work, compared with about three weeks for workers under 35.
Does the research prove AI caused the job losses?
No. The method estimates which job losses were more likely to be associated with AI; it does not establish why an employer eliminated a specific position. The figures are reported estimates, not direct survey responses from workers.
What may help workers after technology-related layoffs?
In Goldman’s historical data, 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 historical associations do not guarantee the same results for workers displaced by AI.
Source: ThorstenMeyerAI.com
