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TL;DR
A Goldman Sachs client note, reported by Fortune on October 30, says workers likely displaced by AI since 2025 took about a month longer to find work and were around 10 percentage points more likely to remain unemployed a year later than other laid-off workers. Goldman’s public research on earlier technology-driven job losses finds longer searches and lasting pay and earnings penalties, though the new AI estimates are indirect and the note is not public.
A Goldman Sachs client note says workers likely displaced by AI since 2025 have taken longer to find new jobs and are more likely to remain unemployed a year later than other laid-off workers, according to a Fortune report published October 30. The estimate suggests the early effects may resemble past technology shocks, when displaced workers often faced extended job searches and lasting pay losses, but Goldman’s new note is not public and its AI classification is indirect.
Fortune reports that Goldman economist Pierfrancesco Mei found likely AI-displaced workers took about one month longer to find new work than comparable laid-off workers. They were also roughly 10 percentage points more likely to still be unemployed one year after losing their jobs. These are figures reported from a client note dated October 29; they have not been independently checked against the note itself, which is not publicly available.
Goldman did not identify AI displacement through a government survey question. Instead, it reportedly analyzed more than 15,000 people who lost jobs from 2016 to 2025, combining 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 score were classified as “likely AI-displaced.” Goldman reportedly found no significant difference between this group and other displaced workers before 2023.
The reported results vary by age. Workers 35 and older took about five weeks longer than comparable laid-off workers to return to full-time work; those under 35 took about three weeks longer. Goldman also found that likely AI-displaced workers were more apt to leave their occupation or industry. Some who returned to work, particularly 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 Extends Beyond Job Loss
The findings shift attention from the number of layoffs to what happens afterward: time out of work, reemployment pay and job stability. A longer search can mean lost income and a more difficult return to secure employment. The reported age differences also point to the possibility that workers may not face the same recovery prospects, although the figures do not establish why older workers took longer.
Goldman’s publicly available historical research provides a longer view. It found that people displaced by earlier technologies took about a month longer to find work and earned more than 3% less in real wages when reemployed than workers laid off from stable or growing occupations. Over the following decade, their real earnings growth was nearly 10 percentage points lower. Those results describe earlier technology shocks, not a proven forecast for every worker affected by AI.
For employers and policymakers, the distinction matters: counting eliminated roles alone does not measure the full cost to workers. Goldman’s historical analysis also found better outcomes among technology-displaced workers who retrained within three years, including about two percentage points more real wage growth over a decade and a roughly 10-point lower chance of becoming unemployed again. That association does not establish that training alone caused the improvement.
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Four Decades of Displacement Data
The new estimate is presented against Goldman research published publicly in a June 2026 “Top of Mind” report and a September summary. Mei and colleagues Jessica Rindels and David Mericle examined more than 300 occupations across decades, drawing on National Longitudinal Surveys that have followed over 20,000 workers through their careers. Their analysis compared people in technology-exposed occupations with workers who were not laid off from those jobs.
Separate government data show age and pay differences among laid-off workers generally, not specifically people displaced by AI. The source material reports 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. Among long-tenured workers who returned to full-time work, about 49% earned as much as before or more, down from about 62% two years earlier, according to the Bureau of Labor Statistics figures cited in the source material.
Goldman’s historical work also found that technology-displaced workers who found new jobs experienced a real-pay reduction while other laid-off workers had negligible losses. The comparison offers context, but it does not show that AI has caused all recent job cuts. Layoffs can have multiple causes, and the available government survey does not ask respondents whether AI cost them their jobs.
““comparable in magnitude””
— Pierfrancesco Mei, Goldman Sachs economist, as quoted in Fortune
How Many Cuts Are AI-Driven?
The central limitation is that AI-caused job loss is not directly measured in the government survey used for Goldman’s estimate. The classification relies on occupational exposure, industry adoption and job elimination, so it identifies workers considered likely to have been displaced by AI rather than confirming the cause of each layoff. The client note is also not public; the reported figures come from Fortune’s account.
It remains unclear how the outcomes differ by education, region or other worker characteristics, and whether the reported patterns will persist as AI adoption changes. The source material does not establish how many layoffs were caused primarily by AI, how many workers were affected in total, or whether workers who changed industries will remain in their new roles. Goldman’s analysis describes associations and estimates, not a settled measure of AI’s overall employment impact.
Tracking the Recovery Over Time
The next evidence will come from following displaced workers over time: whether they regain full-time work, how their wages compare with previous earnings, and whether they remain in new occupations. Additional data could also clarify differences by age, education and region, which Mei said were too early to assess fully.
For now, the reported Goldman note offers an early comparison rather than a final verdict on AI and employment. Its estimates will need to be considered alongside public labor data and further research that can distinguish AI-related job losses from other reasons for layoffs. The historical findings indicate that the effects of displacement can continue well beyond the initial job loss, but the scale and duration of any AI-related impact remain unsettled.
Key Questions
What did Goldman Sachs report about workers likely displaced by AI?
According to Fortune’s account of a Goldman client note, workers likely displaced by AI since 2025 took about one month longer to find work and were roughly 10 percentage points more likely to remain unemployed after a year than other laid-off workers.
How did Goldman identify likely AI-displaced workers?
Goldman reportedly combined an occupation’s AI exposure, the pace of AI adoption in its industry and whether the worker’s position was eliminated. The classification is an estimate; the government survey does not ask whether AI caused a respondent’s job loss.
What did Goldman’s historical research find?
Its public research found that workers displaced by earlier technologies took longer to find jobs, lost more than 3% in real pay when reemployed and experienced weaker real earnings growth over the following decade than comparison workers.
Are the new AI findings publicly available?
The October 29 note was sent to Goldman clients and is not public, according to the source material. The new figures in this article are attributed to Fortune’s report, rather than independently verified against the full note.
Does the research prove AI caused the reported layoffs?
No. Goldman’s method identifies workers who were likely displaced using exposure and adoption indicators, but it cannot confirm the cause of each job loss. The findings are estimates, and the full effects by education, region and other factors remain unclear.
Source: ThorstenMeyerAI.com
