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TL;DR
A Goldman Sachs note reported by Fortune says workers it 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. The findings are preliminary estimates, not a direct count of AI-caused layoffs; Goldman says it is too early to assess outcomes across factors such as education and region.
A Goldman Sachs analysis of workers it estimates were likely displaced by AI since 2025 found they 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. The findings, reported by Fortune, suggest that the consequences of AI-related job losses may resemble earlier technology-driven displacement, but the estimate is not a direct count of layoffs caused by AI.
Goldman economist Pierfrancesco Mei presented the findings in a client note dated Oct. 29. The note is not public; the figures are based on Fortune’s report, which quoted it. Goldman used data from the Labor Department’s Displaced Worker Supplement and assessed more than 15,000 people who lost jobs between 2016 and 2025. It combined occupational exposure to AI, the pace of industry adoption and whether a position was eliminated to identify the top 30% as “likely AI-displaced.”
According to Fortune’s account, the analysis found a longer return to full-time work for older workers in the estimated AI-displaced group: about five weeks longer for workers 35 and older, compared with about three weeks for those under 35. Goldman also found that these workers were more likely to leave their occupation or industry. Some who returned to work, particularly older workers, moved into jobs with similar or higher AI exposure.
Goldman’s public research on earlier technology-related displacement provides a longer-term comparison. It found that affected workers took about a month longer to find work, lost more than 3% in real pay upon reemployment, and experienced nearly 10 percentage points less real earnings growth over the next decade than workers who were not laid off. The historical research also associated retraining within three years with about two percentage points more real wage growth over ten years and a roughly 10-point lower chance of becoming unemployed again.
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 Layoff Day
Layoff totals show how many jobs disappear, but not how long workers remain without work or what their next job pays. Goldman’s reported estimates put those post-layoff outcomes at the center of the AI jobs debate: a longer search, weaker reemployment prospects and possible lasting earnings losses can affect households well after a company announces cuts.
The historical comparison also points to uneven effects. The reported age differences and government figures for laid-off workers generally suggest that older workers may face a harder return, though the government figures cover all long-tenured laid-off workers, not only people displaced by AI. Goldman’s research links retraining with better outcomes, but that relationship does not establish that training alone caused the improvement. The results matter to workers, employers and policymakers weighing how to support people whose roles are changing.
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How Goldman Built Its Comparison
There is no government survey that directly asks whether AI caused someone to lose a job. Goldman therefore constructed a measure from existing layoff data, combining occupation-level AI exposure, industry adoption and job elimination. Its classification is an estimate of likely exposure-related displacement, rather than confirmation of the cause of each individual layoff. Goldman reportedly found no significant difference between its likely AI-displaced group and other laid-off workers for job losses before 2023, when AI adoption began to rise.
The longer-run comparison comes from Goldman research published in June and September 2026. Researchers followed workers across more than 300 occupations using National Longitudinal Surveys covering over 20,000 people. Separately, Bureau of Labor Statistics data cited in the source material 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. Those figures are for laid-off workers overall, not an AI-specific group. The BLS data also show that about 49% of long-tenured workers who returned to full-time work earned as much as before or more, down from about 62% two years earlier.
““comparable in magnitude””
— Pierfrancesco Mei, Goldman Sachs economist, as quoted in Fortune’s report
Limits of the Early AI Estimate
The client note is not publicly available, and its figures in this account come from Fortune’s reporting, not an independent review of the underlying analysis. The method identifies workers as likely displaced using exposure and industry indicators; it cannot establish that AI caused each job loss. The reported results should be read as an early estimate, not a definitive measure of AI’s effect on employment.
It is also unclear how the outcomes vary by education, location or other worker characteristics. The source material says Goldman expects AI-related job losses to accelerate if economic growth slows, while finding that displacement costs are larger in downturns; those are research conclusions and expectations, not confirmation of a future recession or a particular pace of layoffs. The full note’s assumptions and detailed statistical results have not been made public in the cited reporting.
Watch Reemployment and Pay Data
The next useful evidence will be whether the estimated gaps persist as more workers move through job searches and into new roles. Further analysis could clarify how outcomes differ by age, education and region, and whether workers who change industries find jobs with lower exposure to AI. Public labor-market data can track employment and pay trends, but do not by themselves identify AI as the cause of a layoff.
Goldman’s warning about downturns makes the broader economy another factor to watch: if hiring weakens, displaced workers may face longer searches. For now, readers should distinguish the new, reported estimate from the historical findings, which cover earlier technology-driven job losses and offer context rather than a forecast of exactly what will happen to workers affected by AI.
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 after job losses since 2025.
Does the analysis prove that AI caused these layoffs?
No. Goldman used occupational AI exposure, industry adoption and job elimination to identify workers it considered likely AI-displaced. The method estimates a group; it does not confirm the cause of each individual job loss.
What did Goldman’s historical research find about pay?
Goldman’s public research found that workers displaced by earlier 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 were not laid off.
Did older workers have worse outcomes?
In the AI-related estimates reported by Fortune, workers aged 35 and older took about five weeks longer to return to full-time work, compared with about three weeks for those under 35. Separate government figures show an age gap among long-tenured laid-off workers overall, not specifically AI-displaced workers.
What remains unknown about the findings?
The client note is not public, the AI-displacement measure is an estimate, and Goldman says it is too early to assess outcomes across factors such as education and region. The results also do not establish how future economic conditions will affect AI-related job losses.
Source: ThorstenMeyerAI.com
