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TL;DR
Goldman Sachs estimates that workers likely displaced by AI since 2025 took about a month longer to find new jobs than other laid-off workers and were more likely to remain unemployed a year later. The estimates were reported by Fortune from a client note that is not public; Goldman’s historical research links technology-related job loss to lasting wage and employment costs.
Workers Goldman Sachs identifies 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, according to a client note reported by Fortune. The finding matters because it suggests the costs of AI-related layoffs may continue well beyond the date a job is eliminated, although the estimates are not independently confirmed and the note is not public.
The figures come from a Goldman Sachs note dated October 29, reported by Fortune business editor Nick Lichtenberg the next day. Goldman distributes such notes to clients; the source article says its author could not review the note directly. The reported numbers should therefore be treated as estimates relayed through Fortune, rather than independently verified findings. Other coverage cited in the source repeats Fortune’s figures.
Goldman reportedly examined more than 15,000 people who lost jobs between 2016 and 2025, using the U.S. Labor Department’s Displaced Worker Supplement to the Current Population Survey. Because the survey does not ask whether AI caused a job loss, the economists combined occupational exposure to AI, the pace of industry adoption and whether a position was eliminated into a score. Workers in the top 30% were classified as “likely AI-displaced.” Goldman reportedly found no significant gap between this group and other laid-off workers for job losses before 2023.
For workers displaced since 2025, the note reportedly found longer job searches, a higher chance of unemployment a year later and age differences. Those aged 35 and older took about five weeks longer than comparable laid-off workers to return to full-time work, versus about three weeks for workers under 35. The reported analysis also found that displaced workers were more likely to leave their previous occupation or industry, but some who returned to work—especially older workers—entered 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 Cost After the Layoff
The findings shift attention from the number of jobs cut to what happens to workers afterward: time out of work, pay in the next job and the stability of reemployment. A longer search can create financial strain, while moving into a different occupation may mean losing experience, seniority or a career path. The reported Goldman analysis does not establish that AI alone caused each person’s job loss, but it points to a group whose job-market recovery may be slower.
The potential costs extend beyond the first return to employment. Goldman’s public historical research finds that workers displaced by earlier technologies experienced lower real pay after reemployment and weaker real earnings growth over time than workers who were not laid off. If the early AI pattern persists, a new job may not fully restore a worker’s previous economic position. The source material also says Goldman expects AI-related losses to accelerate if economic growth slows, and finds that displacement costs are larger in downturns; those are Goldman’s assessments, not confirmed forecasts of future layoffs.
For employers and policymakers, the evidence makes the quality of reemployment relevant alongside layoff totals. The source reports that retraining was associated in Goldman’s historical data with better wage growth and a lower chance of becoming unemployed again. That association does not by itself prove training caused the improvement, but it suggests why support after displacement may affect whether workers regain stable, comparable work.
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Four Decades of Technology Displacement
The comparison with earlier technology shifts comes from Goldman’s public research, including a June 2026 “Top of Mind” report and a September summary by Pierfrancesco Mei, Jessica Rindels and David Mericle. The economists tracked workers across more than 300 occupations, drawing on National Longitudinal Surveys that have followed over 20,000 people through their careers. They compared workers in occupations most exposed to technology in each decade with workers in more stable or growing occupations.
Goldman’s historical findings, as summarized in the source, show that technology-displaced workers took about one month longer to find work and lost more than 3% in real pay when reemployed, compared with negligible pay loss among the comparison group. Over the following decade, their real earnings growth was nearly 10 percentage points lower. The source also reports 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 historical patterns offer a comparison, not proof that AI’s effects will be identical.
Government data cited in the source show that recovery can vary by age among long-tenured workers, though those figures cover layoffs generally rather than AI-linked job losses. 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. The source also reports that about 49% of long-tenured workers who returned to full-time work earned as much as before or more, down from about 62% two years earlier.
““comparable in magnitude””
— Pierfrancesco Mei, Goldman Sachs economist, as quoted in Fortune’s account of the client note
Limits of the Early AI Estimates
No government survey directly identifies AI-caused job loss, so Goldman’s reported classification is an estimate based on exposure, industry adoption and job elimination. A high score does not establish that AI was the decisive reason a specific worker lost a job. The note is also not public, and its reported results have not been independently checked against the underlying analysis in the source material.
The period covered is short, and the number of workers classified as likely displaced is not provided in the source. It is not clear how results vary by education, location, occupation or other factors; Mei reportedly said it was too early to assess some of those dimensions. Nor does the available account establish whether these workers will ultimately experience the same decade-long wage effects seen in Goldman’s historical research. The source’s retraining figures describe an association, not proof that training alone produced better outcomes.
Tracking Reemployment and Pay
The next useful evidence will show whether the reported job-search gap persists as more workers enter the data and whether those who return to work regain their prior pay. Results broken down by age, education, region and industry could clarify which workers face the greatest difficulties, but those details are not available in the source material. Future research will also need to distinguish AI-driven job elimination from layoffs caused by restructuring, weak demand or other changes.
Readers should watch for further reporting or a public release from Goldman that provides additional methods and results, as well as updates in Labor Department displacement data. For now, the reported estimate is an early signal, not a final measure of AI’s effect on employment. The key test will be whether workers’ recovery follows the slower, lower-paid pattern Goldman found in earlier technology shifts.
Key Questions
What did Goldman Sachs report about workers likely displaced by AI?
According to Fortune’s report on a Goldman client note, workers classified as likely AI-displaced since 2025 took about a month longer to find work and were roughly 10 percentage points more likely to remain unemployed a year later than other laid-off workers.
Are the AI layoff figures confirmed government statistics?
No. The Labor Department survey used in the analysis does not ask whether AI caused a job loss. Goldman reportedly estimated likely displacement using occupational AI exposure, industry adoption and whether a position was eliminated. The note is not public, and its figures are reported through Fortune.
How did outcomes differ by age?
The reported note says 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. These are estimates from the reported AI analysis, not government figures specific to AI layoffs.
What does Goldman’s historical research say about technology layoffs?
Goldman’s public research found that workers displaced by earlier technologies took longer to find work, lost more than 3% in real pay on reemployment and had nearly 10 percentage points less real earnings growth over the following decade than workers who were not laid off.
Does retraining prevent the effects of an AI-related layoff?
The source says Goldman’s historical data linked retraining within three years to about two percentage points more real wage growth over ten years and a roughly 10-point lower chance of becoming unemployed again. That is an association in historical data, not proof that retraining alone caused the difference or a guarantee for workers displaced by AI.
Source: ThorstenMeyerAI.com
