🔍 Read the full analysis: Could AI Layoffs Leave Scars Like Those From Earlier Tech Shocks? on ThorstenMeyerAI.com
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TL;DR
A Goldman Sachs client note, 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. Goldman’s historical research links earlier technology-related job losses to slower reemployment and weaker long-term earnings, but the new estimates are preliminary and the note is not public.
A Goldman Sachs client note dated October 29 estimates 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. The findings, reported by Fortune, raise the possibility that AI-related layoffs could carry employment costs similar to earlier technology shocks, though Goldman says it is too early to assess the full effects.
The note was written by Goldman economist Pierfrancesco Mei and is not publicly available. The figures are based on Fortune’s account, which says it quoted the note directly; they have not been independently confirmed from the original document. Goldman’s estimates rely on a proxy rather than a survey asking people whether AI caused their job loss, because no government survey currently asks that question.
According to Fortune, Goldman analyzed more than 15,000 people who lost jobs between 2016 and 2025, using Labor Department displaced-worker data. It combined occupations’ exposure to AI, industry adoption rates and whether a position was eliminated into a score; the highest-scoring 30% were classified as “likely AI-displaced.” Goldman reportedly found no significant employment-outcome gap for this group before 2023, when AI adoption began to rise.
For job losses since 2025, the note reportedly found that workers aged 35 and older took about five weeks longer than comparable laid-off workers to return to full-time work, compared with about three weeks for those under 35. AI-displaced workers were also more likely to leave their former occupation or industry. Among those rehired, some—especially older workers—entered roles with similar or higher AI exposure, Fortune reported.
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 Can Outlast the Layoff
The estimates matter because they shift attention from the number of positions eliminated to what happens to workers afterward: how long they are unemployed, what they earn when rehired, and whether the new job lasts. A longer job search can mean lost income and a harder return to stable work. The early Goldman results do not establish that AI caused each worker’s displacement, but they suggest that workers in AI-exposed jobs may face a more difficult recovery than other people who lose jobs.
Goldman’s public research on earlier technology-related job losses offers a longer view. It found that displaced workers took about one month longer to find work, earned more than 3% less in real terms on reemployment, and experienced nearly 10 percentage points less real earnings growth over the following decade than workers who were not laid off. Those historical findings do not prove that AI layoffs will produce the same outcomes. They show why the duration and quality of reemployment are important measures of the impact.
The risk may be greater for older workers. Separate Labor Department figures in the source material show that by January 2026, 72.9% of long-tenured workers aged 25 to 54 were working again, compared with 57.3% of those aged 55 to 64. These figures cover long-tenured displaced workers generally, not only people whose jobs were linked to AI. They indicate an age gap in reemployment, but do not identify its causes.
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Four Decades of Job-Loss Data
Goldman’s comparison draws on its publicly released 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 over several decades and tracked workers using National Longitudinal Surveys covering more than 20,000 people. Their historical analysis compared people in technology-exposed occupations who lost jobs with workers laid off from stable or growing occupations.
In that research, technology-displaced workers took longer to return to work and lost more than 3% in real pay when they did. Their real earnings then grew nearly 10 percentage points less over ten years than those of workers who were never laid off. Goldman also reported better outcomes among displaced workers who retrained within three years: roughly two percentage points more real wage growth over ten years and a roughly 10-point lower chance of becoming unemployed again. These are historical associations, not guarantees that retraining will produce the same results for current workers.
The new analysis is based on a different, indirect method and a much shorter period. It identifies people whose job losses are associated with AI-exposed work and industries; it does not directly establish that AI was the reason each person was laid off. That distinction is central when interpreting the reported results.
““comparable in magnitude””
— Pierfrancesco Mei, Goldman Sachs economist, as quoted in Fortune
How Much AI Caused the Displacement
The new estimates are reported secondhand: the Goldman note was sent to clients and is not publicly available, and Fortune is the cited source for its figures. The analysis also uses a constructed measure of likely AI displacement, not workers’ direct accounts or a confirmed causal test. It cannot show that AI, rather than other business or economic factors, caused a particular layoff.
The sample of job losses since 2025 offers only an early view. It is not yet clear whether the reported differences will persist, how outcomes vary by location, education or occupation, or whether workers who move into jobs with similar AI exposure will face further disruption. The source material also reports that the share of long-tenured workers who returned to full-time work at equal or higher pay fell to about 49%, from about 62% two years earlier; that figure concerns displaced workers overall and does not establish an AI-specific trend.
Tracking Reemployment and Pay
The next evidence to watch is whether later data show the same pattern as more workers affected by workplace AI can be followed over time. Useful measures include time to reemployment, full-time work, pay after displacement and repeat unemployment, broken out by age, occupation and region. Government surveys that directly ask whether AI contributed to a job loss could help distinguish AI displacement from other reasons for layoffs.
Goldman’s historical work points to retraining as one factor associated with better outcomes, but the available material does not identify a particular program or establish that any specific intervention will prevent wage losses. The bank also finds displacement costs are larger during downturns and expects AI-related job losses to accelerate if the economy slows. Whether a recession occurs, and how it would affect this group, remain unknown.
Key Questions
What did Goldman Sachs report about workers likely displaced by AI?
According to Fortune’s report on a Goldman client note, workers likely displaced by AI since 2025 took about one month longer to find work than other laid-off workers and were roughly 10 percentage points more likely to remain unemployed a year later.
Does the analysis prove that AI caused these job losses?
No. Goldman reportedly used a score based on occupational AI exposure, industry adoption and whether a position was eliminated. It is a proxy for likely AI displacement, not proof that AI caused an individual worker’s layoff.
Are the Goldman findings publicly available?
The October 29 client note is not public, according to the source material. The current figures are reported from Fortune’s account of the note, rather than independently checked against the original document.
What does Goldman’s historical research say about technology layoffs?
Goldman’s public research found that workers displaced by earlier technological change took longer to find work, earned more than 3% less in real pay when rehired and had nearly 10 percentage points less real earnings growth over the next decade than workers who were never laid off.
Did retraining improve outcomes in the historical data?
Goldman reported that 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. Those historical associations do not guarantee the same outcome for current workers.
Source: ThorstenMeyerAI.com
