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TL;DR
A Goldman Sachs client note dated Oct. 29, 2026, estimates that workers likely displaced by AI since 2025 took about a month longer to find jobs than other laid-off workers and were roughly 10 percentage points more likely to remain unemployed a year later. The note is not public, and its estimates depend on an indirect method for identifying AI-related job losses; Goldman’s published historical research finds similar long-term costs after earlier technology-related displacement.
Workers Goldman Sachs classifies 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 note is not publicly available, and the estimates rely on an indirect measure of AI-related job loss, so they are not a government count of confirmed AI layoffs.
Goldman economist Pierfrancesco Mei compared workers deemed likely to have lost jobs to AI with other displaced workers. Fortune reported the findings on Oct. 30, citing the note, which was dated Oct. 29. Because Goldman distributes the note to clients, the figures in the report have not been independently checked against the full document.
No government survey directly asks whether a worker lost a job because of AI. Goldman instead used the Labor Department’s Displaced Worker Supplement to the Current Population Survey, examining more than 15,000 people who lost jobs between 2016 and 2025. It combined occupational exposure to AI, the pace of AI adoption in an industry, and whether a position had been eliminated. Workers in the top 30% of its resulting score were classified as “likely AI-displaced.”
Fortune reported that, among workers in this group who lost jobs since 2025, those aged 35 and older took about five weeks longer than comparable laid-off workers to return to full-time work; the difference for workers under 35 was about three weeks. The analysis also found that AI-displaced workers were more likely to leave their former occupation or industry, though some who found jobs 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 Can Outlast the Layoff
The figures point to a possible consequence beyond the number of positions eliminated: how quickly displaced people find work, whether their new jobs pay as much, and whether they stay employed. A longer search can mean a longer spell without earnings, while a job in another occupation or industry may require workers to accept different conditions or use different skills. Those are potential effects, not outcomes established for every person labeled likely AI-displaced in Goldman’s estimate.
Goldman’s public historical research offers a longer view. Its work on earlier waves of technological change found displaced workers took about one month longer to find work and lost more than 3% in real pay upon reemployment, compared with workers who had not been laid off. Their real earnings growth over the following decade was nearly 10 percentage points lower. Historical averages do not establish that today’s AI-affected workers will follow the same path, but they make the quality and durability of reemployment relevant alongside headline layoff totals.
The results also suggest that age and economic conditions may shape the impact. Goldman’s reported age differences indicate that older workers may take longer to return to full-time employment. Its historical analysis also links displacement costs to downturns, when openings may be harder to find. That makes the timing of layoffs and the availability of suitable work important to the eventual cost for workers and employers.
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Earlier Technology Losses Offer a Benchmark
The comparison draws on Goldman research published in its June 2026 “Top of Mind” report and a September summary by Mei and colleagues Jessica Rindels and David Mericle. That public work tracked workers across more than 300 occupations, using National Longitudinal Surveys that have followed more than 20,000 people through their careers. Goldman compared workers in occupations exposed to technological change with those in stable or growing occupations.
In that historical analysis, workers displaced by technology took longer to find another job, experienced an average real-pay decline of more than 3% when reemployed, and had weaker real earnings growth over the next decade. Goldman also reported better outcomes among technology-displaced workers who retrained within three years: about 2 percentage points more real wage growth over ten years and a roughly 10-point lower chance of becoming unemployed again. These are historical associations reported in Goldman’s research, not a guarantee that retraining will produce the same result for each worker.
For the newer estimate, Goldman found no significant difference between its likely AI-displaced group and other laid-off workers for job losses before 2023, according to Fortune’s account. The firm used that as a check against its classification method. It does not remove the uncertainty involved in inferring the reason for an individual layoff from occupation and industry data.
““comparable in magnitude””
— Pierfrancesco Mei, Goldman Sachs economist, as quoted in Fortune
AI Layoff Counts Remain Unverified
The Goldman note is not public, and Fortune’s report is the source for its specific estimates. The figures should be treated as reported findings, not independently confirmed measurements. Other outlets repeating the numbers do not provide a separate underlying dataset or public version of the note.
The classification is also an estimate: no government survey directly identifies AI as the cause of a job loss. A worker may lose a position in an AI-exposed occupation or industry for other reasons, and the score cannot by itself establish that AI caused a particular layoff. Goldman said its analysis was still too early to assess differences across dimensions including education and region. The reported results also do not establish how many U.S. layoffs since 2025 were caused by AI.
More Data Will Test the Estimate
The next steps are clearer evidence on the causes of job losses and follow-up on how displaced workers fare over time. As later Labor Department survey data become available, researchers may be able to compare job searches, reemployment, pay, and unemployment across worker groups. But without a survey that asks directly whether AI caused a job loss, estimates will continue to depend on proxies such as occupation exposure and industry adoption.
Goldman’s published historical research points to retraining and economic conditions as relevant factors, but the new reported note does not settle what support works best for workers currently affected. The duration of job searches, the pay and stability of replacement work, and differences by age, education, and region remain areas to watch. Any later claims about a faster pace of AI-related job loss will also need to be judged against observed employment data, not exposure estimates alone.
Key Questions
What did Goldman Sachs estimate about workers likely displaced by AI?
Fortune reported that workers Goldman classified as likely AI-displaced since 2025 took about one month longer to find work than other laid-off workers and were roughly 10 percentage points more likely to remain unemployed a year later.
Are these figures confirmed government statistics?
No. The estimates come from a Goldman client note reported by Fortune, and the note is not public. The government survey Goldman used records displaced workers but does not directly ask whether AI caused their job loss.
How did Goldman identify likely AI-related job losses?
Goldman combined an occupation’s AI exposure, the pace of AI adoption in its industry, and whether a position was eliminated. It classified workers in the top 30% of its score as “likely AI-displaced.” That method estimates a connection; it cannot confirm the cause of any individual layoff.
Did older workers face longer searches?
According to Fortune’s account of the note, workers aged 35 and older took about five weeks longer than comparable laid-off workers to return to full-time work. For workers under 35, the reported gap was about three weeks.
What remains unknown about the effects?
The number of layoffs directly caused by AI, the longer-term pay and job stability of affected workers, and differences by education and region remain unclear. Goldman said it was too early to assess all of those dimensions.
Source: ThorstenMeyerAI.com
