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TL;DR
A Goldman Sachs note dated October 29, 2026, reported by Fortune, estimates that workers likely displaced by AI since 2025 have taken about a month longer to find new jobs than other laid-off workers. Goldman’s historical research finds that technology-related job losses have also been linked to lower pay and slower earnings growth, though the newer AI estimates rely on an indirect measure and have not been independently confirmed here.
Workers likely displaced by AI since 2025 have taken about a month longer to find new work than other laid-off workers, according to a Goldman Sachs analysis reported by Fortune. The finding links the emerging effects of AI-related job loss to a longer historical pattern in which workers displaced by technology faced slower reemployment and lasting pay setbacks.
The Goldman analysis was included in a client note dated October 29. Fortune reported the next day that economist Pierfrancesco Mei and colleagues estimated that workers classified as likely displaced by AI were roughly 10 percentage points more likely than other laid-off workers to remain unemployed a year after losing their jobs. Goldman’s note is not public; the figures in the new analysis are reported through Fortune and have not been independently verified here.
Because government surveys do not ask whether AI caused a specific job loss, Goldman constructed a proxy using more than 15,000 people laid off between 2016 and 2025. It combined occupational exposure to AI, the pace of AI adoption in an industry and whether a position was eliminated. Workers in the top 30% of the resulting measure were labeled “likely AI-displaced.” Goldman reportedly found no significant difference between that group and other laid-off workers before 2023.
For job losses since 2025, the note also reported an age divide: workers aged 35 and older took about five weeks longer than comparable laid-off workers to return to full-time work, while those under 35 took about three weeks longer. The analysis reportedly found that AI-displaced workers were more likely to leave their previous occupation or industry, but 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 cost extends beyond the layoff
The reported findings shift attention from the number of positions cut to what happens to workers afterward. A longer search can mean an extended period without wages, while a lower-paying next job can affect household finances well beyond the initial loss. Goldman’s estimates suggest that the consequences may also differ by age, with older workers taking longer to return to full-time employment.
The historical evidence makes the issue relevant even while the AI-specific data remain preliminary. Goldman’s public research finds that workers displaced by technology took about one month longer to find new 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 findings describe earlier technology-related displacement, not a guaranteed outcome for today’s AI-affected workers.
For employers and policymakers, the distinction matters: counting layoffs alone does not capture the potential duration or quality of workers’ recovery. Goldman’s historical analysis also links retraining within three years to about 2 percentage points more real wage growth over ten years and a roughly 10-point lower chance of becoming unemployed again. That is an association in the research, not proof that retraining alone caused the difference.
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Four decades of technology displacement
Goldman’s comparison draws on its public research, including a June 2026 “Top of Mind” report and a September summary by Mei, Jessica Rindels and David Mericle. The researchers examined more than 300 occupations and followed workers through National Longitudinal Surveys that track more than 20,000 people over their careers. They compared workers in occupations most exposed to technology in each decade with workers who were laid off from more stable or growing occupations.
The historical research found that reemployed technology-displaced workers lost more than 3% in real pay, while their real earnings grew nearly 10 percentage points less over the next decade than those of workers who were never laid off. Separately, government figures cited in the source material show an age gap among long-tenured workers: by January 2026, 72.9% of those aged 25 to 54 were working again, compared with 57.3% of those aged 55 to 64. These figures cover laid-off workers generally, not just people displaced by AI.
Pay recovery has also weakened in the broader group of long-tenured workers who returned to full-time jobs. The source material cites Bureau of Labor Statistics data showing about 49% earned as much as before or more, compared with about 62% two years earlier. That comparison does not isolate AI-related job losses.
“Comparable in magnitude”
— Pierfrancesco Mei, Goldman Sachs economist, as quoted in Fortune
AI job losses remain hard to isolate
The central limitation is that the new estimate is not a direct count of people who say AI took their jobs. Goldman used a constructed measure of occupational exposure, industry adoption and position elimination, then classified the top 30% as likely displaced. That approach can identify patterns, but it cannot establish that AI caused each job loss.
The underlying October note was sent to Goldman clients and is not publicly available. The reported figures therefore depend on Fortune’s account, rather than a public copy that readers can inspect. Goldman also said it was too early to assess effects across dimensions including education and region. The analysis does not establish how many jobs AI has caused to disappear overall, whether the reported outcomes will persist, or how much of the difference reflects AI rather than other factors.
More data will test the pattern
The next test will be whether later labor-market data show the same differences in job-search duration, reemployment and pay as more workers experience workplace changes involving AI. A public release of Goldman’s full methods and results would allow researchers to examine the estimates directly, including how the AI-displacement measure was constructed and how sensitive the findings are to its assumptions.
Goldman’s historical research also points to the importance of tracking what happens after reemployment: whether workers return to full-time roles, what those jobs pay and whether they remain employed. The note reportedly warns that displacement costs are larger during downturns and that AI-related job losses could accelerate if the economy slows. That is a forecast, not a confirmed outcome; the scale and timing of any future acceleration remain unknown.
Key Questions
What did Goldman Sachs report about workers likely displaced by AI?
In a client note dated October 29, 2026, Goldman estimated that workers 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. Fortune reported the findings; the note itself is not public.
How did Goldman identify likely AI-related job losses?
Goldman reportedly combined occupational exposure to AI, the pace of AI adoption in an industry and whether a position was eliminated. Workers in the top 30% of that measure were classified as likely AI-displaced. It is a proxy, not a direct survey response confirming that AI caused a particular job loss.
Do the findings show that all laid-off workers face the same outcomes?
No. The reported Goldman estimate found a difference by age: workers aged 35 and older took about five weeks longer to return to full-time work than comparable laid-off workers, while those under 35 took about three weeks longer. The analysis also found workers more likely to move out of their former occupation or industry.
What does the historical research say about technology layoffs?
Goldman’s public research found that workers displaced by technology took about a month longer to find new jobs, 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 were never laid off. These are historical findings, not predictions for every worker affected by AI.
What remains unknown about the AI findings?
The estimate cannot confirm that AI caused each job loss, and the client note is not publicly available for independent review. Goldman also said it is too early to assess effects across areas such as education and region, or to know whether the reported patterns will continue.
Source: ThorstenMeyerAI.com
