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TL;DR
A Goldman Sachs 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 longer-term research on past technology-related layoffs finds lasting pay and earnings losses, though the new AI estimates are based on an indirect measure and remain preliminary.
Workers likely displaced by AI since 2025 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 new Goldman Sachs estimate reported by Fortune. The findings matter because Goldman’s research on earlier technology-driven layoffs suggests that the effects can extend beyond the initial job loss, including lower pay and weaker earnings over time.
Fortune reported that Goldman found the likely AI-displaced group took about one month longer than other displaced workers to find new work and was roughly 10 percentage points more likely to still be unemployed one year after losing a job. Goldman economist Pierfrancesco Mei’s note was sent to clients and is not publicly available; the figures in the new analysis are therefore reported through Fortune rather than independently checked against the note.
Goldman did not identify workers who said AI directly caused their job loss. Instead, its researchers built an estimate from Labor Department survey data covering more than 15,000 people who lost jobs between 2016 and 2025. The score combined 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 measure were classified as “likely AI-displaced.” Goldman reportedly found no significant difference between that group and other laid-off workers before 2023, when AI adoption began to rise.
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 workers under 35 took about three weeks longer. The likely AI-displaced workers were also more likely to leave their previous occupation or industry. Some who found work again, particularly older workers, entered roles with similar or higher AI exposure, according to Fortune’s account.
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 Long Cost of Losing a Job
The reported figures put attention on what happens after a layoff, not just how many positions disappear. A longer search can mean a longer period without wages, while a move into a different occupation may involve lower pay or work that is less stable. Those effects may be especially difficult for older workers, who in the Goldman estimate took longer to return to full-time employment.
Goldman’s public research on past technology-related job losses offers a reason to track outcomes over years. It found that workers displaced by technology took about one 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 grew nearly 10 percentage points less, according to the research summarized in the source material. These historical results do not establish what will happen to today’s AI-displaced workers, but they suggest that reemployment alone may not mean a return to the same economic position.
The research also points to differences among workers and economic conditions. The source reports that retraining within three years was associated in Goldman’s historical data with about 2 percentage points more real wage growth over ten years and a roughly 10-point lower likelihood of becoming unemployed again. Goldman also found displacement costs were larger during downturns. Those are associations and historical findings, not a guarantee that retraining will produce the same result for any individual.
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What Earlier Technology Layoffs Show
The comparison draws on Goldman research published publicly in June 2026 and summarized in September. Mei, Jessica Rindels and David Mericle studied workers across more than 300 occupations, identifying occupations most exposed to technology in each decade and following workers through National Longitudinal Surveys. The surveys have tracked more than 20,000 people over their careers, according to the source material.
In that historical analysis, technology-displaced workers had slower reemployment and lower real pay than workers laid off from stable or growing occupations. The source also reports a broader pay pressure among long-tenured workers who returned to full-time jobs: about 49% earned as much as before or more, compared with about 62% two years earlier, citing Bureau of Labor Statistics data. That statistic concerns long-tenured workers generally, not only workers displaced by AI.
The new estimate is a separate analysis of recent job losses. Since no government survey asks whether AI caused a person’s job loss, Goldman used its exposure-and-adoption measure as a proxy. The measure can identify workers whose jobs fit a pattern associated with AI exposure, but it cannot establish that AI was the reason each person was laid off.
““comparable in magnitude””
— Pierfrancesco Mei, Goldman Sachs economist, as quoted in Fortune
Limits of the AI Displacement Estimate
The estimates do not prove that AI caused the layoffs in the group Goldman classified as likely AI-displaced. The method relies on occupation exposure, industry adoption and position elimination, rather than workers’ own reports or a confirmed record of why an employer cut a job. The client note itself is also not public, and the reported figures have not been independently verified here.
The analysis covers job losses since 2025, leaving a relatively short period in which to observe outcomes. It is not yet clear whether the reported patterns will persist, how results differ by education or region, or how many workers are affected. Nor does the historical comparison show that AI will produce the same long-term effects as previous technologies. The Goldman research describes a pattern in past data, not a settled forecast for current workers.
What Future Labor Data Can Clarify
The next step is to see whether additional labor-market data supports the reported pattern as more workers move through job searches and into new roles. Longer follow-up would help show whether the one-year unemployment gap persists and whether reemployed workers recover their former pay, remain in a different occupation or face another job loss.
Goldman’s note, as reported, flags education and region as areas where the effects are still too early to assess. Future analyses could also help distinguish AI-related displacement from other reasons for layoffs and compare outcomes across age groups and industries. Until then, the figures should be read as an early estimate set against historical research—not a final count of jobs lost to AI or a prediction of any individual worker’s prospects.
Key Questions
How many AI-displaced workers did Goldman identify?
The reported analysis does not provide a confirmed count of workers whose jobs were caused to disappear by AI. Goldman classified the top 30% of a measure combining AI exposure, industry adoption and position elimination as likely AI-displaced.
How long did likely AI-displaced workers take to find new jobs?
Fortune reported that they 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 after losing their jobs.
Were older workers more affected?
In the reported Goldman estimate, workers aged 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.
Does the study prove that AI caused these layoffs?
No. Goldman used an indirect measure because government surveys do not ask workers whether AI cost them their jobs. The findings identify a group likely exposed to AI-related displacement; they do not confirm the cause of each layoff.
What does Goldman’s historical research say about retraining?
In the historical data described in the source material, technology-displaced workers who retrained within three years had about 2 percentage points more real wage growth over ten years and a roughly 10-point lower chance of becoming unemployed again. This association does not guarantee the same outcome for future workers.
Source: ThorstenMeyerAI.com
