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TL;DR
A Goldman Sachs client note, reported by Fortune on Oct. 30, estimates that workers likely displaced by AI since 2025 took about a month longer to find new jobs than other laid-off workers and were roughly 10 percentage points more likely to remain unemployed a year later. The figures are estimates, not a direct count of AI-caused job losses, and the private note has not been independently reviewed here. Goldman’s public research on earlier technology-related layoffs finds longer-term risks to pay and earnings, while retraining is associated with better outcomes.
A Goldman Sachs analysis of workers who lost jobs since 2025 estimates that those likely displaced by AI 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. Fortune reported the findings on Oct. 30, citing a Goldman client note dated the previous day; the note is not public, and the figures are estimates rather than a government count of AI-caused layoffs.
Goldman economist Pierfrancesco Mei and colleagues constructed a measure of likely AI displacement because government surveys do not ask workers whether AI caused their job loss. As described in Fortune’s report, the researchers used Labor Department data on displaced workers and considered occupational exposure to AI, industry adoption and whether a position was eliminated. They classified the top 30% of their resulting scores as likely AI-displaced.
The analysis covered more than 15,000 workers who lost jobs from 2016 to 2025. Goldman reportedly found no significant difference in outcomes between the likely AI-displaced group and other laid-off workers before 2023, when AI adoption began to rise. For job losses since 2025, the reported gap included a longer search for new work and a higher likelihood of still being unemployed after a year.
The report also described an age difference: workers 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. Likely AI-displaced workers were also more likely to leave their previous occupation or industry. Some who found new jobs, especially older workers, reportedly 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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Longer Searches Could Deepen Pay Losses
The length of a job search matters because a layoff can affect workers well after the initial loss of income. Goldman’s public research on earlier technology-related displacement finds that affected workers took about one month longer to find a job and lost more than 3% in real pay when reemployed, compared with negligible losses among workers laid off from stable or growing occupations. Over the following decade, their real earnings growth was nearly 10 percentage points lower.
Those historical findings do not prove that AI-displaced workers will experience the same long-term effects. They do show why the new estimate is relevant beyond the number of jobs cut: a longer search, a lower-paying next role or repeated unemployment can compound the cost for households. The reported age gap also suggests that recovery may vary across workers rather than follow a single pattern.
Goldman’s historical analysis links retraining within three years of a technology-related job loss to about 2 percentage points more real wage growth over ten years and a roughly 10-percentage-point lower chance of becoming unemployed again. That is an association in the research, not a guarantee that training alone causes better outcomes or that the same results will apply to current AI-related layoffs.
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Comparing AI With Earlier Tech Shocks
The new client note draws on Goldman’s earlier, public work on technology-related job loss. A June 2026 Goldman report and a September summary tracked workers across more than 300 occupations, using career data from National Longitudinal Surveys that followed more than 20,000 workers. Researchers identified occupations most exposed to technology in each decade and examined what happened to people who held those jobs.
That historical analysis found slower reemployment and weaker pay and earnings growth for workers displaced by technology. It also found larger costs during economic downturns. Goldman’s economists expect AI-related job losses to accelerate if the economy slows, but that is a forecast, not a confirmed outcome. The historical research offers a comparison point; it does not establish that AI will affect all workers or occupations in the same way.
For current labor-market comparisons, Bureau of Labor Statistics data cited in the source material show differences among long-tenured workers who lost jobs. By January 2026, 72.9% of those 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. These figures cover laid-off workers generally, not people identified as displaced by AI.
““Comparable in magnitude””
— Pierfrancesco Mei, Goldman Sachs economist, as quoted in Fortune’s report
AI Job Losses Remain Hard to Measure
The estimate depends on a proxy rather than a direct report from workers. The Displaced Worker Supplement does not ask whether AI caused a layoff, so Goldman’s classification combines exposure, industry adoption and position elimination. The top 30% of scores are labeled likely AI-displaced; that method cannot establish that AI was the reason for each individual job loss.
The findings also come from a private Goldman client note described by Fortune, not a public paper independently assessed here. Fortune is the source for the new figures, and other coverage repeating them does not amount to separate confirmation. The full note, its detailed methods and the underlying calculations were not available in the source material.
Goldman’s reported analysis covers job losses since 2025, leaving a relatively short period for observing outcomes. It is not yet clear how results differ by education, region, occupation or other worker characteristics, or whether the estimated gaps will persist as AI adoption changes. The recession-related warning is a forecast, not evidence that a downturn or a specific acceleration in layoffs has occurred.
Tracking Reemployment and Pay Over Time
The next test is whether workers classified as likely displaced continue to show longer job searches, lower reemployment rates or weaker pay as more labor-market data become available. Longer follow-up would help show whether the reported one-year unemployment gap persists and whether workers who change industries or occupations find stable work.
Further detail from Goldman could clarify the scoring method, the limits of the comparison and the results by age, education and region. Government surveys do not currently identify AI as the cause of a job loss, so future estimates will still need careful labeling unless data collection changes. For now, the reported analysis should be read as an early estimate, while Goldman’s historical findings provide context rather than a definite forecast for the current group.
Key Questions
What did Goldman Sachs estimate about workers displaced by AI?
According to Fortune’s report on a Goldman client note, workers classified as likely AI-displaced since 2025 took about one month longer to find work and were roughly 10 percentage points more likely to remain unemployed a year later than other laid-off workers.
Does the estimate prove AI caused those workers’ layoffs?
No. Government surveys do not ask whether AI caused a job loss. Goldman used a measure combining occupational AI exposure, industry adoption and whether a position was eliminated, then classified the top 30% of scores as likely AI-displaced.
Why might older workers face a harder recovery?
The note, as reported by Fortune, estimated that 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. The reported analysis does not establish why the gap occurred.
Goldman’s public historical research found that workers displaced by technology took longer to find work, lost more than 3% in real pay when reemployed and had weaker real earnings growth over the next decade than workers laid off from stable or growing occupations.
Can retraining prevent the long-term effects?
Goldman’s historical data associated retraining within three years with about 2 percentage points more real wage growth over ten years and a roughly 10-percentage-point lower chance of becoming unemployed again. This is an association, not a guarantee or proof that the same results will apply to AI-displaced workers.
Source: ThorstenMeyerAI.com
