🔍 Read the full analysis: How AI Layoffs Echo Four Decades Of Technology Shocks, According To Goldman Sachs on ThorstenMeyerAI.com
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TL;DR
A Goldman Sachs note, reported by Fortune, estimates that workers likely displaced by AI since 2025 take about a month longer to find work and are roughly 10 percentage points more likely to remain unemployed a year later than other laid-off workers. The note’s figures are not independently confirmed in the source material, and Goldman says it is too early to assess impacts across factors such as education and region. The findings resemble the longer-lasting employment and wage costs Goldman has documented for workers displaced by earlier technologies.
Workers likely displaced by AI since 2025 have taken about a month longer to find new jobs and were roughly 10 percentage points more likely to remain unemployed a year after losing work than other laid-off workers, according to a Goldman Sachs note reported by Fortune. The estimate suggests the early effects of AI-related job loss may resemble the persistent employment and pay costs Goldman has identified in earlier technology shifts, though the client note is not public and its figures have not been independently verified in the supplied reporting.
Goldman economist Pierfrancesco Mei compared workers estimated to have been displaced by AI with other laid-off workers. Fortune reported the findings on October 30, one day after the note was dated. Because Goldman distributes the note to clients, the source article says its author could not examine it directly; the reported numbers should be treated as reported findings, not independently confirmed data.
The analysis used the Labor Department’s Displaced Worker Supplement to the Current Population Survey and covered more than 15,000 people who lost jobs between 2016 and 2025. Goldman reportedly combined occupational AI exposure, industry adoption of AI and whether a position was eliminated to classify the top 30% of the resulting score as “likely AI-displaced.” The source says Goldman found no significant gap between this group and other laid-off workers for job losses before 2023.
For losses since 2025, Fortune reported that 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 those under 35. Goldman also reportedly found that AI-displaced workers were more likely to leave their occupation or industry. Some who found jobs, particularly older 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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Longer Searches, Lasting Pay Costs
The findings matter because the cost of a layoff is not limited to the day a position ends. A longer job search can mean more time without earnings, while a lower-paid return to work can affect a household’s finances well beyond the initial disruption. Goldman’s reported estimate of a 10-percentage-point difference in unemployment after a year points to a potentially uneven recovery for workers whose jobs are exposed to AI.
Goldman’s public historical research provides a basis for concern, but not proof that the current AI wave will follow precisely the same path. Its research on earlier technology-related displacement found workers took about one month longer to find work, lost more than 3% in real pay when reemployed, and experienced nearly 10 percentage points less real earnings growth over the following decade than workers who were never laid off. Those figures describe historical groups and should not be confused with the newer, AI-focused estimates.
The implications also extend to employers and policymakers. If workers cannot readily move into stable jobs with comparable pay, the economic effects may persist after headline layoff counts fall. The Goldman note reportedly finds that retraining was associated with better outcomes in historical data, but the source does not establish that training alone caused those gains or that the same results will apply to today’s AI-displaced workers.
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Four Decades of Displacement Data
The comparison draws on Goldman research published publicly in a June 2026 “Top of Mind” report and a September summary by Mei and colleagues Jessica Rindels and David Mericle. They examined more than 300 occupations and used National Longitudinal Surveys that have followed more than 20,000 workers over their careers. The researchers tracked workers in occupations most exposed to technology in each decade and compared their outcomes with other workers.
In that historical research, people displaced by technology took around a month longer to find work and lost more than 3% in real pay when reemployed, compared with negligible pay losses among workers laid off from stable or growing occupations, according to the source. Their real earnings growth over the following decade was nearly 10 percentage points lower than for workers who were never laid off. The source also reports that workers who retrained within three years had about two percentage points more real wage growth over ten years and were roughly 10 percentage points less likely to become unemployed again. These are associations reported in historical data.
Government figures cited in the source show that reemployment outcomes vary by age even among long-tenured workers laid off for any reason. 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 employment, about 49% earned as much as or more than before, down from about 62% two years earlier, the source says, citing the Bureau of Labor Statistics. These figures are not limited to AI-related layoffs.
““comparable in magnitude””
— Pierfrancesco Mei, Goldman Sachs economist, as quoted in Fortune
Limits of the Early AI Estimate
No government survey directly asks workers whether AI caused them to lose a job. Goldman therefore constructed an estimate using a score based on occupational exposure, industry adoption and whether a position disappeared. That approach identifies workers considered likely to have been affected; it does not establish the cause of each individual job loss.
The new note is not public, and the source’s account relies on Fortune’s reporting and its quotations from the note. The reported figures have not been independently checked here. The analysis also covers job losses since 2025, leaving limited time to observe longer-term outcomes. Mei said it was too early to assess effects across dimensions such as education and region. It is also unclear from the supplied material how the estimates may change as AI adoption, hiring and economic conditions develop.
Goldman reportedly expects AI-related job losses to accelerate if the economy slows and finds that displacement costs are greater during downturns. That is an assessment about risk, not confirmation that a recession will occur or that layoffs will rise by a particular amount.
Tracking Reemployment and Pay
The next evidence will come from whether workers laid off in the recent period find jobs, how long their searches last and what happens to their pay after reemployment. Longer follow-up would help distinguish an initial delay from the lasting earnings effects seen in Goldman’s historical research. Future data may also clarify which occupations, age groups and regions face the largest changes.
For now, readers should treat the AI-specific results as an early estimate reported from a private client note, rather than a government count of confirmed AI layoffs. Goldman’s public historical research offers a comparison, while the Department of Labor’s survey provides broader layoff and reemployment measures. Further reporting or public analysis of the method and underlying figures could allow closer scrutiny of how the AI-displacement group was defined.
Key Questions
What did Goldman Sachs report about workers likely displaced by AI?
According to Fortune’s account of a Goldman client note, workers estimated to have lost jobs to AI 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.
Are these figures confirmed government statistics?
No. The source says the figures come from a non-public Goldman note reported by Fortune. Goldman built an estimate because government surveys do not directly ask whether AI caused a worker’s job loss. The reported numbers have not been independently verified in the supplied material.
How did Goldman identify likely AI-displaced workers?
Goldman reportedly combined occupational AI exposure, industry AI adoption and whether a position was eliminated into a score. Workers in the top 30% were classified as likely AI-displaced. The method estimates exposure; it does not confirm the cause of each person’s layoff.
Goldman’s public research found that workers displaced by earlier technologies 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 were never laid off.
Does the report show that retraining prevents job loss?
No. The source says historical data linked retraining within three years to about two percentage points more real wage growth over ten years and a roughly 10-percentage-point lower chance of becoming unemployed again. Those associations do not establish that retraining caused the improved outcomes or guarantee similar results for workers displaced by AI.
Source: ThorstenMeyerAI.com
