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TL;DR
A Goldman Sachs note, reported by Fortune on Oct. 30, says workers likely displaced by AI since 2025 took about a month longer to find new jobs than other laid-off workers. The estimate is based on a model, not a government measure of AI-caused layoffs, while Goldman’s historical research links technology displacement to lasting wage and employment costs.
Goldman Sachs estimates that workers who likely lost jobs to AI 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. Fortune reported the findings from a client note dated Oct. 29; the note is not public, and the figures are based on a model rather than a government count of AI-caused job losses.
According to Fortune, Goldman economist Pierfrancesco Mei and colleagues estimated AI displacement by examining more than 15,000 people who lost jobs between 2016 and 2025. They combined measures of occupational exposure to AI, the pace of adoption in a worker’s industry and whether the position was eliminated. Workers in the top 30% of the resulting score were classified as “likely AI-displaced.” The account of the private note comes through Fortune; the source material says other coverage repeats its figures.
The reported gap appeared for job losses since 2025. Goldman found no significant difference between the modeled group and other laid-off workers for losses before 2023, according to Fortune. Workers aged 35 and older reportedly took about five weeks longer than comparable laid-off workers to return to full-time employment; for those under 35, the difference was about three weeks. The reported analysis also found that AI-displaced workers were more likely to leave their previous occupation or industry.
Goldman’s separate, public research examines earlier waves of technological change. It found that workers displaced by technology took about a month longer to find work, lost more than 3% in real pay when reemployed, and had nearly 10 percentage points less real earnings growth over the next decade than workers who had not been laid off. Those historical results are not a direct measurement of AI layoffs, but provide a comparison for the new estimates.
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 After the Layoff
The estimates shift attention from the number of jobs cut to what happens to workers afterward: time out of work, pay in a new role and the durability of reemployment. If the reported pattern holds as AI adoption expands, a layoff may affect earnings and job stability well beyond the initial period without work. The findings do not establish that AI caused every job loss included in Goldman’s model, or that every displaced worker will experience the same outcome.
The historical research also suggests that getting hired again does not necessarily restore a worker’s previous financial position. Goldman’s public findings associate technology-related displacement with lower real pay and weaker earnings growth over time. They point to the possibility that the consequences of AI-related job cuts could be measured in years, not only in the interval between jobs.
Goldman’s historical analysis, as summarized in the source material, found better outcomes among workers who retrained within three years: roughly 2 percentage points more real wage growth over a decade and a roughly 10-point lower chance of becoming unemployed again. This is an association in the research, not proof that retraining alone caused the difference or a guarantee of similar results for today’s workers.
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Four Decades of Displacement Data
Goldman’s long-run comparison draws on research described in its June 2026 “Top of Mind” report and a September summary by Mei and colleagues Jessica Rindels and David Mericle. They tracked workers across more than 300 occupations using National Longitudinal Surveys that have followed over 20,000 workers through their careers. The researchers identified occupations with greater exposure to technology in each decade and followed workers who held those jobs.
That work offers a historical benchmark, not a forecast that AI will reproduce earlier changes in every detail. The new estimate uses the Labor Department’s Displaced Worker Supplement to the Current Population Survey, but the source material says no government survey asks respondents whether AI caused them to lose a job. Goldman therefore constructed a proxy using exposure, adoption and job elimination. Its reported check found no significant gap between the proxy group and other displaced workers before 2023, when AI adoption began to rise.
Government figures cited in the source material show age differences among long-tenured workers who had lost jobs, regardless of whether AI was involved. By January 2026, 72.9% of those aged 25 to 54 were working again, compared with 57.3% of those aged 55 to 64. Among long-tenured workers who returned to full-time work, about 49% earned as much as before or more, down from about 62% two years earlier, according to Bureau of Labor Statistics data. These figures describe laid-off workers overall, not a confirmed AI-displaced group.
““comparable in magnitude””
— Pierfrancesco Mei, as quoted in Fortune’s account of the Goldman Sachs note
Limits of the AI Job Estimate
The central uncertainty is whether Goldman’s proxy correctly identifies people whose jobs were lost because of AI. Its score combines several indicators, but it is not a direct survey response or a verified count of AI-caused layoffs. The note itself is not public, so readers depend on Fortune’s account for the reported figures and methodology.
The results also cover an early period of AI adoption and may not describe later outcomes. Mei said it was too early to assess impacts across education and regional groups. It is unclear from the available account how the estimated effects vary across occupations, industries or types of AI use, or how many workers in the modeled group lost jobs primarily because of AI rather than other business changes.
The source material says Goldman expects AI-related job losses to accelerate when the economy slows, and that displacement costs are larger in downturns. That is an expectation based on the research, not confirmation that a recession will occur or that future AI layoffs will follow a particular path. The analysis does not establish whether retraining or other interventions would produce the same results for workers affected by AI today.
Tracking Reemployment and Pay
The next evidence will come from whether the reported employment gap persists as more workers lose jobs during wider AI adoption. Future labor-market data may clarify how quickly affected workers find new roles, whether they return to full-time work and how their inflation-adjusted earnings compare with pay before displacement.
Goldman’s note, as described by Fortune, identifies education and region as areas where effects remain unassessed. A public version of the note or further research with clearer measures of AI-caused job loss could help test the estimate. Until then, the figures should be read as an early model-based assessment alongside longer-term historical evidence—not as a definitive count of AI layoffs or a settled prediction of their effects.
Key Questions
What did Goldman Sachs report about AI-displaced workers?
According to Fortune’s account of a Goldman client note, workers classified as likely AI-displaced since 2025 took about a month longer to find new work and were roughly 10 percentage points more likely to remain unemployed a year later than other laid-off workers.
Does the estimate count confirmed AI-caused layoffs?
No. Goldman used a model combining occupational AI exposure, industry adoption and whether a position was eliminated. The source material says there is no government survey that directly asks whether AI caused a respondent’s job loss.
What do earlier technology layoffs suggest?
Goldman’s public historical research found that technology-displaced workers took longer to find new jobs, lost more than 3% in real pay when reemployed, and experienced weaker real earnings growth over the following decade than workers who had not been laid off.
Were older workers affected differently?
Fortune reported that workers aged 35 and older in Goldman’s modeled AI-displaced group took about five weeks longer to return to full-time work, compared with about three weeks for those under 35. Separate government data also show lower reemployment rates among long-tenured workers aged 55 to 64 than among those aged 25 to 54, but those figures are not specific to AI.
What remains uncertain?
The estimate’s accuracy, the number of jobs actually lost because of AI, and the effects by education, region and occupation remain unclear. The reported results cover an early period and are based on a private note described by Fortune, not a public government count.
Source: ThorstenMeyerAI.com
