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TL;DR
Goldman Sachs estimates that workers likely displaced by AI since 2025 took about a month longer to find work and were roughly 10 percentage points more likely to remain unemployed a year later than other laid-off workers. The findings, reported by Fortune from a client note that is not public, echo Goldman’s historical research on technology-related job losses and their lasting effects on pay and employment.
Workers Goldman Sachs classifies as likely displaced by AI have taken longer to find new jobs and have been more likely to remain unemployed a year later than other laid-off workers, according to a client note reported by Fortune. The findings, based on job losses since 2025, suggest that the employment costs of AI may extend beyond the initial layoff and resemble damage associated with earlier technology-driven job losses.
The note, dated October 29, 2026, was written by Goldman economist Pierfrancesco Mei and sent to clients. Goldman’s note is not public; the figures in the new analysis are reported by Fortune, which said it quoted the note directly. They have not been independently verified from the note itself.
As reported, workers classified as likely displaced by AI took about one month longer to find a new job than other laid-off workers. They were also roughly 10 percentage points more likely to still be unemployed one year after losing their jobs. 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.
Goldman’s classification is an estimate, not a direct count of people who say AI cost them their jobs. Fortune reported that the bank analyzed more than 15,000 workers who lost jobs between 2016 and 2025, scoring occupations according to AI exposure, industry adoption and whether a position was eliminated. The top 30% of scores were labeled “likely AI-displaced.” Goldman reportedly found no significant difference between that group and other laid-off workers for job losses before 2023.
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 Costs Can Follow Workers
The findings focus attention on what happens after a layoff: the time spent searching, the type of work people find and whether their earnings recover. A longer period without work can affect household income, while a lower-paying next job can carry costs well beyond the initial disruption. Goldman’s new estimates are preliminary, but they suggest that workers facing AI-linked job loss may need support beyond severance or short-term job placement.
Goldman’s public research on earlier technology-related job losses gives the new estimates a longer historical frame. That research found that displaced workers took about a month longer to find work and lost more than 3% in real pay when reemployed. Over the next decade, their real earnings grew nearly 10 percentage points less than those of workers who had not been laid off. These historical results do not prove that AI will produce the same outcomes, but they show why employment statistics alone may not capture the full effect of displacement.
The reported age gap also matters for employers and policymakers. If older workers take longer to return to full-time jobs, training and placement programs may need to address different barriers for different groups. Goldman’s historical analysis, as summarized in the source material, links retraining within three years to about two 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 a guarantee that training will produce those results for every worker.
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A New Estimate, Set Against History
There is no government survey that asks laid-off workers whether AI caused their job loss. Goldman’s method therefore tries to identify likely cases by combining measures of occupational exposure, industry adoption and whether the role was eliminated. The result is a modeled group, not a confirmed tally of AI-caused layoffs. A worker in a high-exposure occupation may have lost a job for reasons unrelated to AI.
Goldman’s public historical work, published in a June 2026 “Top of Mind” report and a September summary, tracked workers across more than 300 occupations using National Longitudinal Surveys that have followed over 20,000 people through their careers. The research compared workers in occupations more exposed to technological change with workers laid off from stable or growing occupations. It found slower reemployment, lower pay after reemployment and weaker earnings growth over time among technology-displaced workers.
The new note compares its estimated AI-displaced group with other laid-off workers, while the historical research examines earlier technology shocks over several decades. Those are related but distinct analyses. The historical pattern offers context; it does not establish that AI-related layoffs will have identical causes, scale or long-term effects.
““comparable in magnitude””
— Pierfrancesco Mei, Goldman Sachs economist, as quoted in Fortune
How Much AI Caused the Losses
The central limitation is that AI displacement is estimated, not directly reported. The method identifies workers whose occupations and industries fit a set of AI-related measures; it cannot establish that AI was the reason each person was laid off. The note’s underlying data and full methodology are not publicly available, and the results here are reported by Fortune rather than independently checked against the client note.
The sample also covers a short period of rising AI adoption. It is not yet clear whether the reported differences will persist as more workers are observed, or how outcomes vary by education, region and industry. Nor do the reported figures establish how many jobs AI has eliminated overall. Goldman’s historical findings and the new estimate provide a comparison, not a forecast of the scale or duration of future losses.
More Data Will Test the Pattern
The next test will be whether workers losing jobs in later years show the same gaps in reemployment and pay as the group in Goldman’s estimate. Longer follow-up would help show whether the reported one-year unemployment difference persists and whether people move into stable work or continue through temporary jobs and second jobs.
Further public data or a fuller account of Goldman’s method could also clarify how the bank assigned its AI-displacement scores and how sensitive the results are to those choices. For now, the public historical research supplies relevant context, while the newer AI-related figures remain a reported estimate. The duration and distribution of any longer-term effects remain open questions.
Key Questions
What did Goldman Sachs find about likely AI-displaced workers?
In a client note reported by Fortune, Goldman estimated that workers it classified as likely displaced by AI since 2025 took about a month longer to find new work and were roughly 10 percentage points more likely to remain unemployed a year later than other laid-off workers.
Did Goldman confirm that AI caused these workers’ layoffs?
No. The bank used a scoring method based on occupational AI exposure, industry adoption and whether a position was eliminated. The group is described as “likely AI-displaced”; the method does not confirm the cause of each individual job loss.
Is Goldman’s new analysis publicly available?
The source says the October 29 note was sent to clients and is not public. The new figures are based on Fortune’s report of the note, rather than direct public access to the full analysis.
What does Goldman’s historical research say about technology layoffs?
Goldman’s public research found that workers displaced by earlier technology changes took longer to find work, lost more than 3% in real pay when reemployed and experienced weaker real earnings growth over the following decade than workers who were not laid off.
What remains unknown about the effects of AI layoffs?
It is not yet clear whether the reported employment gaps will persist, how outcomes differ by education or region, or how many layoffs were caused by AI rather than other factors. Goldman reportedly said it was too early to assess all dimensions of the impact.
Source: ThorstenMeyerAI.com
