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TL;DR
A Goldman Sachs client note dated Oct. 29, 2026, says workers it classifies as likely displaced by AI since 2025 took about a month longer to find jobs than other laid-off workers. Fortune reported the findings; Goldman’s method estimates AI displacement, and the note is not public. The figures echo Goldman’s historical research linking technology-related job loss with slower reemployment and weaker earnings.
Workers Goldman Sachs classifies as likely displaced by AI are taking longer to find new jobs than other laid-off workers, according to a client note dated Oct. 29 and reported by Fortune. The estimate suggests the costs of AI-related job loss may extend beyond the initial layoff, but it is based on an indirect measure of displacement, and the note is not publicly available.
Fortune reported that workers who lost jobs since 2025 and fell into Goldman’s “likely AI-displaced” group took about one month longer to find work than other displaced workers. They were also roughly 10 percentage points more likely to remain unemployed a year after losing their jobs. Those figures come from Fortune’s account of the Goldman note, not from a publicly released document that could be checked independently.
Goldman reportedly examined more than 15,000 workers laid off between 2016 and 2025, using Labor Department survey data. It scored each job loss based on the occupation’s exposure to AI, the pace of AI adoption in the industry, and whether the position was eliminated. The top 30% of scores were classified as likely AI displacement. The method is an estimate: government surveys do not directly ask whether AI caused a person’s job loss.
The reported note also found different outcomes by age. 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. The estimates do not establish that AI alone caused each layoff or subsequent delay.
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 Continue After Layoffs
The findings focus attention on what happens after a job loss: the time spent searching, the pay offered in a new role, and whether employment lasts. A longer search can mean lost income and greater difficulty returning to a stable position, even when a worker eventually finds another job.
Goldman’s publicly available historical research adds a longer-term comparison. It found that workers displaced by earlier technological changes took about a month longer to find work and earned more than 3% less in real terms 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. These historical results do not prove that current AI-related layoffs will have the same effects, but they show why job placement alone may not capture the full cost.
For employers and policymakers, the reported age gap and longer-term wage findings point to questions about retraining and support after layoffs. Goldman’s historical data linked retraining within three years to 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 show that retraining guarantees those outcomes.
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Earlier Technology Shocks Offer a Comparison
Goldman’s new estimate draws on its separate public research into earlier waves of technological change. A June 2026 “Top of Mind” report and a September summary by economist Pierfrancesco Mei and colleagues Jessica Rindels and David Mericle tracked workers across more than 300 occupations, using National Longitudinal Surveys that followed over 20,000 people through their careers.
That historical work found slower reemployment and weaker pay outcomes for workers whose jobs were exposed to technology. It also reported that displacement costs were larger during economic downturns. The historical analysis covers past technological shifts, not AI layoffs specifically, so it is a comparison rather than a forecast.
Government data cited in the source material show age differences among long-tenured workers laid off for any reason: by January 2026, 72.9% of those aged 25 to 54 were working again, compared with 57.3% of those aged 55 to 64. Those figures are not limited to AI-related layoffs. The same source says the share of long-tenured workers who regained full-time work and earned as much as before or more was about 49%, down from about 62% two years earlier.
““comparable in magnitude””
— Pierfrancesco Mei, Goldman Sachs economist, as quoted in the Fortune report
How Much AI Caused the Displacement
The central limitation is attribution. The Labor Department survey does not identify AI as the reason for a layoff, so Goldman reportedly used an exposure-and-adoption score to identify workers considered likely to have been displaced by AI. That approach cannot confirm that AI caused a particular job loss, and the top-30% cutoff is a research classification rather than a government count of AI layoffs.
The Goldman note itself is not public. The new figures are reported through Fortune’s account, and the source material says other coverage repeats Fortune’s numbers. The exact results, definitions, and full analysis therefore cannot be independently reviewed from the note.
It also remains unclear whether the current pattern will persist, how it varies by education and region, and how many affected workers eventually return to their previous occupation or pay level. The historical evidence identifies associations across earlier technology shocks; it does not establish the future effects of AI.
More Evidence Needed on Worker Outcomes
The next useful evidence will show whether the longer job searches reported for workers displaced since 2025 continue as more data become available. Further analysis could also clarify differences by age, education, region, and industry, as well as whether workers move into jobs with different pay or AI exposure.
Goldman’s reported note says the effect of a future economic slowdown could be important: its historical research finds larger costs when displacement takes place during downturns. The source material does not give a date for a follow-up report or identify a specific next release. For now, the AI-specific figures should be treated as reported estimates, not a complete count of job losses caused by AI.
Key Questions
What did Goldman Sachs find about AI-related job loss?
As reported by Fortune, workers classified as 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 a year after losing their jobs than other laid-off workers.
Can the figures confirm that AI caused these layoffs?
No. The Labor Department survey does not ask whether AI caused a job loss. Goldman reportedly estimated likely displacement using occupation exposure, industry adoption, and whether a position was eliminated.
Is Goldman’s new analysis publicly available?
The client note is not public, according to the source material. The new figures are based on Fortune’s report of the note, so readers cannot independently review its complete analysis.
What does Goldman’s historical research say about technology layoffs?
Goldman’s public research found that workers displaced by earlier technological changes took longer to find work and faced weaker real-pay outcomes than certain other laid-off workers. Those past findings provide a comparison, not proof that AI will produce identical results.
What remains unknown about the effects of AI layoffs?
The true number of layoffs caused by AI, how results differ by education and region, and whether affected workers regain their previous pay or job stability remain unclear. Goldman has not announced a specific date for further findings in the source material.
Source: ThorstenMeyerAI.com
