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TL;DR
A Goldman Sachs client note, reported by Fortune, says 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 reported findings resemble Goldman’s public research on earlier technology-related job losses, which found persistent effects on pay and earnings. The new estimates are indirect, and the note is not public.
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, according to a Goldman Sachs client note reported by Fortune. The findings echo Goldman’s research on technology-related job losses over four decades, but the new figures are estimates based on an indirect measure of AI exposure, not a government count of AI-caused layoffs.
The note, dated October 29, was written by Goldman economist Pierfrancesco Mei. Goldman’s client research is not public; the figures in the new analysis are based on Fortune’s report, which quotes the note. The source material says other coverage repeated Fortune’s numbers, rather than independently verifying them.
Goldman reportedly examined 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. Because the survey does not ask whether AI caused a job loss, Goldman combined occupational exposure to AI, the pace of AI adoption in an industry and whether a position was eliminated into a score. Workers in the top 30% were classified as “likely AI-displaced.”
For job losses since 2025, the analysis found a longer route back to work and a sharper age gap. Workers aged 35 and older reportedly took about five weeks longer than comparable laid-off workers to return to full-time work; those under 35 took about three weeks longer. The reported analysis also found that AI-displaced workers were more likely to leave their former occupation or industry, while some who found work 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 Long Cost of Job Displacement
The comparison matters because a layoff’s impact is not captured by the number of jobs cut on announcement day. A longer unemployment spell can affect household income, savings and the kind of work a person can secure next. Goldman’s reported estimate suggests that workers identified as likely AI-displaced may face a slower recovery than other people who have also lost jobs.
Goldman’s public historical research adds a longer-term warning, though it does not establish that today’s AI-related workers will have identical outcomes. The firm found that workers displaced by earlier technologies took about one month 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 never laid off. Those findings point to potential lasting costs beyond the initial period without work.
The reported age differences also matter for workers and employers planning retraining or job-placement support. Government figures cited in the source show that among long-tenured workers aged 25 to 54 who lost jobs, 72.9% were working again by January 2026, compared with 57.3% of those aged 55 to 64. These figures cover laid-off workers generally, not people identified as displaced by AI, and should not be read as an AI-specific measure.
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Four Decades of Technology Shifts
Goldman’s comparison draws on publicly released work, including its June 2026 “Top of Mind” report and a September summary by Mei, Jessica Rindels and David Mericle. That research tracked workers across more than 300 occupations and used National Longitudinal Surveys following over 20,000 people through their careers. Goldman identified occupations most exposed to technology in each decade and examined what happened to workers in them.
In that historical research, technology-displaced 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, according to the source material. This is an association reported in Goldman’s analysis, not proof that retraining alone caused the difference or a guarantee of a particular outcome.
The new estimate uses a different, indirect method to identify likely AI displacement. Goldman reportedly found no significant gap between its designated group and other laid-off workers for job losses before 2023, when AI adoption began to rise. That check offers historical comparison, but it does not confirm that AI caused each job loss in the later group.
““Comparable in magnitude””
— Pierfrancesco Mei, Goldman Sachs economist, as quoted in the reported client note
Limits of the AI Displacement Estimate
No government survey directly records AI-caused job losses, and Goldman’s classification relies on occupation, industry adoption and whether a position disappeared. A worker in a highly exposed occupation may have lost a job for other reasons, so “likely AI-displaced” is an analytical category, not a verified cause for every case.
The Goldman note is not publicly available, and the new results here are reported through Fortune rather than independently checked against the underlying analysis. The source also says it is too early to assess differences by education and region. It remains unclear how the estimates will change as more workers are tracked, how much of the trend reflects AI rather than other economic forces, and whether the historical wage and earnings patterns will repeat.
Goldman’s expectation that AI-related job losses could accelerate when the economy slows is a forecast, not a reported outcome. The source says displacement costs have been larger in downturns, but does not provide a specific projection for the number of future AI-related layoffs.
More Evidence as Workers Reenter Jobs
The next test will be whether subsequent data show the longer search periods and weaker reemployment outcomes continuing as AI adoption spreads. More follow-up is needed to compare workers across age, education, region and occupation, and to distinguish AI-related displacement from layoffs caused by broader business or economic changes.
Goldman’s historical findings suggest retraining may be associated with better outcomes, but the available figures do not identify which programs work best or who can access them. A downturn could put additional pressure on displaced workers, according to Goldman’s analysis; whether that risk materializes depends on economic conditions and future hiring. For now, the reported note is an early estimate, not a definitive accounting of AI’s effect on employment.
Key Questions
What did Goldman Sachs find about likely AI-displaced workers?
Goldman’s client note, as reported by Fortune, found that workers likely displaced by AI since 2025 took about one 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.
How did Goldman identify workers likely displaced by AI?
Because the government survey does not ask whether AI caused a job loss, Goldman reportedly combined a job’s AI exposure, AI adoption in the industry and whether the position was eliminated. Workers in the top 30% of its score were labeled “likely AI-displaced.”
Are these confirmed counts of AI-caused layoffs?
No. They are estimates based on an indirect classification, not a count of layoffs whose cause was verified as AI. The new note is not public, and the figures are reported through Fortune.
What does the 40-year comparison show?
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 experienced slower real earnings growth over the following decade than workers who were never laid off. Those historical findings do not guarantee the same outcome for workers affected by AI.
What remains unknown?
It is not yet clear how many job losses were caused specifically by AI, how results vary by education or region, or whether the reported patterns will persist as more workers are followed over time.
Source: ThorstenMeyerAI.com
