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TL;DR
A Goldman Sachs analysis, reported by Fortune, estimates that workers likely displaced by AI since 2025 took about a month longer to find work than other laid-off workers and were more likely to remain unemployed a year later. The findings are estimates, not a direct count of AI-caused layoffs; Goldman’s historical research suggests technology-related job losses can also bring lasting wage penalties.
Workers Goldman Sachs classifies as likely displaced by AI have taken 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 Goldman note reported by Fortune. The analysis suggests the consequences of AI-related job cuts may extend beyond the initial layoff, but the figures are estimates because no government survey directly identifies workers who lost jobs to AI.
The note was dated October 29, 2026, and Fortune reported its findings the next day. Goldman’s note was distributed to clients and was not publicly available, so Fortune’s account is the source for the new figures. They should be treated as reported estimates, not as independently verified counts of AI-caused job losses.
Goldman reportedly examined more than 15,000 people who lost jobs between 2016 and 2025, using Labor Department survey data. It combined occupational exposure to AI, the pace of AI adoption in an industry, and whether a position was eliminated to identify the top 30% as “likely AI-displaced.” The analysis found no significant difference between that group and other laid-off workers for job losses before 2023, according to Fortune’s account.
The reported results also show a difference by age: workers aged 35 and older took about five weeks longer than comparable laid-off workers to return to full-time employment, while those under 35 took about three weeks longer. Goldman reportedly found that displaced workers were more likely to leave their previous occupation or industry, although some who found new work—especially older workers—moved into jobs 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 Recovery Can Outlast the Layoff
The findings shift attention from the announcement of job cuts to the duration and quality of recovery. A longer search can mean more time without wages, while a lower-paying next job can affect earnings well after a worker is rehired. Goldman’s new estimate concerns unemployment timing; its separate historical research points to a broader risk of persistent pay and earnings losses after technology-related displacement.
The stakes are not limited to people who lose jobs. Employers making AI-related staffing decisions, workers considering retraining, and policymakers tracking labor-market effects all need to know whether displaced workers return quickly, find comparable work, or move into less secure or lower-paid roles. The reported analysis offers an early signal, not a definitive measure of AI’s overall employment impact.
Age may shape how quickly people return to full-time work, but the figures do not establish why. Workers’ occupations, locations, education, and the availability of comparable openings could also matter. Goldman reportedly said it was too early to assess some of these differences, including those by education and region.
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Four Decades of Technology Displacement
The new estimate is presented alongside Goldman’s public research on earlier technology-related job losses. In a June 2026 Top of Mind report and a September summary, economist Pierfrancesco Mei and colleagues Jessica Rindels and David Mericle tracked workers across more than 300 occupations, drawing on National Longitudinal Surveys that have followed over 20,000 people through their careers.
Goldman’s historical analysis found that workers displaced from occupations exposed to technological change took about one month longer to find new work than workers laid off from stable or growing occupations. On reemployment, they lost more than 3% in real pay, according to the source material. Over the following decade, their real earnings grew nearly 10 percentage points less than those of workers who had not been laid off.
Historical outcomes also varied with retraining. Goldman’s research associated retraining within three years of displacement with about two percentage points more real wage growth over ten years and a roughly 10-percentage-point lower chance of becoming unemployed again. These are reported associations; they do not establish that retraining alone caused the difference or guarantee similar results for workers affected by AI.
““comparable in magnitude””
— Pierfrancesco Mei, Goldman Sachs economist, as quoted in Fortune’s account of the client note
How Much Was Caused by AI?
No government survey asks workers whether AI cost them their jobs, so Goldman used an exposure-and-adoption score rather than direct confirmation from workers or employers. The “likely AI-displaced” category is therefore an analytical classification; it does not prove that AI caused each individual layoff. The client note itself is not public, and the new figures rely on Fortune’s reporting.
The reported findings cover a limited early period and do not establish how outcomes will change as AI adoption spreads. It is also unclear how results vary by region, education, occupation, or other worker characteristics. The source material says Goldman expects AI-related job losses to speed up if the economy slows and finds displacement costs are larger in downturns; these are expectations and historical patterns, not confirmation of what will happen in a future recession.
More Evidence From Workers’ Outcomes
The next question is whether the longer searches reported for workers displaced since 2025 persist as more labor-market data become available. Future analysis will need to distinguish jobs eliminated by AI from roles affected by broader company changes or economic conditions, and to track time out of work, reemployment pay, and job stability separately.
Goldman’s historical findings point to retraining as one factor associated with better outcomes, but the available material does not specify which programs work best or whether they are accessible to the workers most affected. The evidence also remains too early to show whether AI-exposed workers will follow the same long-term pattern as workers displaced by past technologies.
Key Questions
How much longer did likely AI-displaced workers take to find jobs?
Fortune reported that Goldman estimated they took about one month longer than other laid-off workers to find new work. The figure comes from a client note that was not publicly available.
Does the analysis prove that AI caused these layoffs?
No. Goldman classified workers using occupational AI exposure, industry adoption, and whether a position was eliminated. Since government surveys do not directly ask whether AI caused a job loss, the category is an estimate of likely displacement, not proof for each case.
Were older workers affected differently?
According to Fortune’s account of Goldman’s note, 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.
What does Goldman’s earlier research say about wages?
Goldman’s public historical research found that workers displaced by technology lost more than 3% in real pay when reemployed and had nearly 10 percentage points less real earnings growth over the following decade than workers who had not been laid off.
Source: ThorstenMeyerAI.com
