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TL;DR
A Goldman Sachs client note, reported by Fortune on Oct. 30, 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 roughly 10 percentage points more likely to remain unemployed a year later. The estimates are not based on a government survey asking whether AI caused a job loss, and the note is not public; Goldman’s longer-term research on technology-related displacement points to lasting wage and employment costs.
Workers Goldman Sachs classifies as likely displaced by AI since 2025 took about a 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, according to a client note reported by Fortune. The figures suggest that the consequences of AI-related job cuts may resemble earlier technology-driven displacement, but Goldman’s estimate is indirect and the note is not publicly available.
Goldman economist Pierfrancesco Mei wrote the note dated Oct. 29, according to Fortune business editor Nick Lichtenberg’s report the following day. Because the note was sent to clients, the figures in the report cannot be independently checked against the original document from the supplied material. The source article says other outlets repeated Fortune’s numbers.
Goldman reportedly analyzed more than 15,000 people who lost jobs between 2016 and 2025 using the Labor Department’s Displaced Worker Supplement to the Current Population Survey. It combined occupational exposure to AI, the pace of AI adoption in a worker’s industry and whether the position was eliminated. Workers in the top 30% of the resulting score were categorized as “likely AI-displaced.” Goldman found no significant difference in outcomes for this group and other laid-off workers before 2023, according to the report.
For job 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; workers under 35 took about three weeks longer. The note also reportedly found AI-displaced workers were more likely to leave their former occupation and industry, while some who returned to work entered roles with similar or greater 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 After an AI Layoff
The estimates shift attention from the number of announced cuts to what follows: time out of work, the quality of reemployment and pay recovery. If displaced employees take longer to find a job or return at lower pay, the effects of automation can persist beyond the initial redundancy and reach household finances and career paths.
Goldman’s historical research suggests those consequences can last. Its public work, as summarized in the source material, finds technology-displaced workers took about one month longer to find another job and lost more than 3% in real pay upon reemployment, compared with negligible losses for workers laid off from stable or growing occupations. Over the following decade, their real earnings growth was nearly 10 percentage points lower. Those historical results do not prove that AI-related layoffs will produce the same long-term effects, but they offer a basis for concern and comparison.
The reported age gap also matters for workforce planning. Older workers may face a longer return to full-time employment, while people who move into another role with high AI exposure could remain vulnerable to further changes. The source material reports that retraining was associated with better long-term outcomes in Goldman’s historical data, but does not establish that training alone caused those gains.
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How Goldman Built the Comparison
There is no government survey in the source material that asks laid-off workers directly whether AI caused their job loss. Goldman therefore used an estimate based on worker, occupation and industry characteristics, rather than a count of confirmed AI layoffs. Its classification covered the top 30% of its exposure-and-adoption score; it should not be read as a verified list of people who lost jobs because of AI.
The comparison draws on separate, public Goldman research from June 2026 and a September summary. Mei and colleagues Jessica Rindels and David Mericle tracked workers across more than 300 occupations using National Longitudinal Surveys that have followed more than 20,000 people through their careers, according to the source article. That work examined earlier technology-related displacement over several decades and found slower job searches, pay losses and weaker long-term real earnings growth.
Government figures cited in the source provide a wider, but not AI-specific, view of reemployment. Among long-tenured workers aged 25 to 54 who had been displaced, 72.9% were working again by January 2026, compared with 57.3% of those aged 55 to 64. The source also says that among long-tenured workers who regained full-time work, about 49% earned as much as before or more, down from about 62% two years earlier. These figures concern displaced workers generally, not people confirmed to have lost jobs to AI.
““comparable in magnitude””
— Pierfrancesco Mei, Goldman Sachs economist, as quoted in Fortune
Limits of the AI Layoff Estimate
AI-caused job losses are not directly identified in the government survey Goldman used. The analysis infers likely displacement from exposure, industry adoption and position elimination. That method may group together workers whose jobs ended for different reasons, and the source material does not provide enough detail to assess the sensitivity of the results to the scoring choices.
The Goldman note itself is not public, so its calculations and full qualifications are available here only through Fortune’s account. The reported sample covers job losses through 2025, and the results do not establish what will happen to future workers as AI adoption changes. Mei also said it was too early to assess effects across education and regional groups. It remains unclear how the outcomes vary across industries, how much of the age gap reflects factors other than AI exposure, and whether reported reemployment outcomes lead to sustained work.
What New Data Could Show
The next step is to track whether workers identified as likely AI-displaced find lasting jobs, what those jobs pay and whether their new roles remain exposed to automation. Further analysis across age, education, region and industry could clarify which groups face the longest searches and weakest wage recovery. The supplied source does not identify a scheduled release date for a follow-up analysis.
For now, the reported Goldman estimate is an early signal, not a definitive count or forecast. Its conclusions can be tested as more job-loss and reemployment data become available, including through future updates to public labor statistics and further research. Until then, the historical comparison offers context for the potential costs, while leaving the scale and distribution of AI’s effects unsettled.
Key Questions
What did Goldman Sachs estimate about AI-related job losses?
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 new work and were roughly 10 percentage points more likely to remain unemployed a year after losing a job than other laid-off workers.
Does the estimate count confirmed AI layoffs?
No. Goldman reportedly used a score based on occupational AI exposure, industry adoption and whether a position was eliminated. The government survey it analyzed does not directly ask whether AI caused a worker’s job loss.
Were older workers affected differently?
Fortune reported that workers 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. These are estimates from the Goldman note, not independently verified results in the supplied source.
What does Goldman’s historical research say about technology layoffs?
The public research summarized in the source material found technology-displaced workers took 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.
What is still unknown about AI’s effects on workers?
The number of job losses directly caused by AI, long-term outcomes for affected workers and differences by education, region and industry remain unclear. Goldman’s reported analysis is an early estimate, and its client note is not publicly available.
Source: ThorstenMeyerAI.com
