🔍 Read the full analysis: After AI Layoffs, Workers Face Questions That Past Tech Shocks Raised on ThorstenMeyerAI.com
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TL;DR
A Goldman Sachs client note, reported by Fortune, estimates that workers likely displaced by AI since 2025 took about a month longer to find new work than other laid-off workers and were more likely to remain unemployed a year later. Goldman’s historical research links technology-related job loss to lasting pay and earnings setbacks, but the new AI figures rely on an estimate rather than a government count of AI-caused layoffs.
Workers Goldman Sachs classifies as likely displaced by AI since 2025 took about a month longer to find another job than other laid-off workers and were roughly 10 percentage points more likely to remain unemployed a year later, according to a client note reported by Fortune. The estimates suggest that the consequences of AI-related job loss may extend beyond the initial layoff, though the note is not public and there is no government survey that identifies AI as the cause of a worker’s job loss.
The estimates come from a Goldman Sachs note dated October 29 by economist Pierfrancesco Mei. Fortune reported the findings the next day, quoting the note; Goldman’s client research is not publicly available, so the figures have not been independently checked against the underlying analysis. Goldman compared workers it deemed likely to have been displaced by AI with other people who had lost jobs.
Because official labor surveys do not ask whether AI caused a job loss, Goldman constructed an estimate using the Labor Department’s Displaced Worker Supplement. The analysis covered more than 15,000 people who lost jobs between 2016 and 2025. It combined occupational exposure to AI, the speed of AI adoption in an industry and whether a position was eliminated. Workers in the top 30% of the resulting score were labeled “likely AI-displaced.” Goldman reportedly found no significant difference between that group and other laid-off workers for job losses before 2023.
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 a year after losing a job. 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. The note also reported that AI-displaced workers were more likely to leave their former occupation and industry, but some rehired workers 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 Costs Continue After Layoffs
The findings shift attention from the number of positions cut to what happens to workers afterward: how long reemployment takes, whether the next job pays as much and whether displaced people find stable work. A longer search can mean more time without earnings, while a lower-paying job can affect household finances well after someone returns to employment.
Goldman’s public research on earlier technology-driven job losses offers a historical comparison, not proof of what will happen to every worker affected by AI. That research found that workers displaced by technology took about a month longer to find work and earned more than 3% less in real pay after reemployment. Their real earnings grew nearly 10 percentage points less over the following decade than those of workers who had not been laid off. The evidence points to potential long-term costs, while the new AI-specific estimates remain early and model-dependent.
The results also raise questions for employers and policymakers about support after a job ends. Goldman’s historical analysis associated retraining within three years with roughly 2 percentage points more real wage growth over ten years and a roughly 10-point lower chance of becoming unemployed again. Those figures describe an association in the historical data; they do not establish that retraining alone caused the better outcomes.
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Comparing AI With Earlier Shocks
Goldman’s comparison draws on research published publicly in a June 2026 “Top of Mind” report and a September summary. Mei and colleagues Jessica Rindels and David Mericle examined more than 300 occupations over several decades, identifying jobs most exposed to technology in each period and tracking workers through the National Longitudinal Surveys, which follow more than 20,000 people over their careers.
That research found technology-displaced workers faced slower reemployment and weaker wage outcomes than workers laid off from stable or growing occupations. Separately, Labor Department data show that returning to work can be harder for older long-tenured workers across layoffs generally: by January 2026, 72.9% of workers aged 25 to 54 in that group were working again, compared with 57.3% of those aged 55 to 64. These government figures cover laid-off workers broadly, not people identified as displaced by AI.
The pay outlook for people who return to full-time work has also weakened in the cited government data. About 49% of long-tenured workers who found full-time work again earned as much as or more than before, compared with about 62% two years earlier. That change is not an AI-specific measure and should not be read as evidence that AI caused the decline.
““comparable in magnitude””
— Pierfrancesco Mei, Goldman Sachs economist, as quoted in the client note reported by Fortune
Limits of the AI Job Estimate
The reported figures are estimates, not a direct count of people whose jobs were taken by AI. The government survey used in the analysis records displaced workers but does not establish why each job ended. Goldman’s scoring method combines exposure, industry adoption and job elimination, and the report does not make every individual case a confirmed AI-caused layoff.
The underlying client note is not public. The reported findings therefore cannot be checked here against its full methods, tables or assumptions, and Fortune is the cited source for the new figures. It is also unclear how results differ by education, region or other worker characteristics; Mei said it was too early to assess some of those dimensions. The figures do not establish that AI, rather than other factors, caused any particular worker’s unemployment or pay change.
More Evidence From Future Layoffs
The next test will be whether later data show the reported gaps persisting as AI adoption and job losses evolve. Government surveys currently do not identify AI as the cause of displacement, leaving researchers to rely on estimates such as Goldman’s rather than a direct official measure.
For workers, the near-term outcomes to watch are the length of job searches, return to full-time employment and pay after reemployment, particularly for older workers. Goldman’s historical findings suggest retraining may be associated with better outcomes, but the available material does not show which programs work best or whether the same pattern will hold for AI-displaced workers. Further conclusions will depend on additional data and on publication of the methods behind the new estimate.
Key Questions
What did Goldman Sachs report about workers likely displaced by AI?
According to figures in its client note reported by Fortune, workers Goldman classified as likely AI-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.
Does the government count AI-related layoffs?
Not directly in the survey used for this analysis. Goldman said it estimated likely AI displacement by combining occupational AI exposure, industry adoption and job elimination. That method does not confirm AI caused each individual layoff.
Are older workers facing a longer return to work?
The note’s reported estimates say workers aged 35 and older 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. Separate government figures show an age gap among long-tenured laid-off workers generally, not an AI-specific group.
Goldman’s public research found that workers displaced by technology earned more than 3% less in real pay after finding new work and had weaker real earnings growth over the following decade than workers who had not been laid off. Those historical findings do not predict the outcome for every worker displaced by AI.
What remains unknown about the new findings?
The underlying note is not public, and the reported AI-displacement figures are estimates rather than direct survey counts. The available reporting also leaves open how outcomes vary by education, region and other factors, and whether the early job-search patterns will persist.
Source: ThorstenMeyerAI.com
