🔍 Read the full analysis: The Aftermath Of AI Layoffs May Sound Familiar To Tech’s Veterans on ThorstenMeyerAI.com
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TL;DR
A Goldman Sachs client note, reported by Fortune, estimates that workers likely displaced by AI since 2025 have taken about a month longer to find work than other laid-off workers and were more likely to remain unemployed a year later. Goldman’s historical research finds that workers displaced by earlier technologies also faced longer searches and lasting earnings losses; the new estimates are based on an indirect measure, not a government count of AI-caused layoffs.
Workers likely displaced by AI since 2025 have taken 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, according to a Goldman Sachs note reported by Fortune. The estimates suggest the aftermath of AI-related job losses may resemble the long-running employment and pay costs associated with earlier technology shifts, though the note uses an indirect measure of AI displacement.
The client note was dated October 29 and written by Goldman economist Pierfrancesco Mei. Goldman’s note is not public; the details in this report come from Fortune’s account, which quoted it. The figures should be treated as reported estimates, not independently verified results from the note.
Because no government survey asks workers whether AI caused their job loss, Goldman constructed a measure using Labor Department data on displaced workers. It examined more than 15,000 people who lost jobs from 2016 to 2025, scoring occupations by AI exposure, industry adoption and whether a position was eliminated. Workers in the top 30% of that measure were classified as “likely AI-displaced.” Goldman reportedly found no significant difference between that group and other laid-off workers for job losses before 2023, when AI adoption began to rise.
For job losses since 2025, Goldman’s reported estimates show a longer job search and a higher chance of still being unemployed after a year. The note also found an age gap: workers 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. Some workers moved out of their former occupation or industry, but reemployed workers—particularly older ones—were more likely to enter jobs 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 Costs Continue After Layoffs
The analysis shifts attention from the number of announced job cuts to what happens to workers afterward: how long they remain out of work, whether they return to full-time employment and how their pay changes. Those outcomes affect household income and the security of a career, and they can persist even after a worker finds another job.
Goldman’s public historical research offers a longer comparison. Its June 2026 report and September summary examined workers in more than 300 occupations across several decades, drawing on National Longitudinal Surveys that followed more than 20,000 people. Goldman found that workers displaced by technology took about a month longer to find new work and earned more than 3% less in real terms when reemployed. Over the following decade, their real earnings growth was nearly 10 percentage points lower than for workers who had not been laid off.
The historical figures do not prove that AI will produce the same results. They do show why reemployment alone may not capture the cost of displacement: workers can return to work but still face reduced pay growth or repeated joblessness. Goldman’s historical analysis also linked 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 reported by Goldman, not proof that retraining by itself caused the difference.
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A New Estimate, an Older Pattern
Goldman’s current estimate is not a direct count of people whose employers explicitly cited AI as the reason for a layoff. Instead, it combines occupational exposure, industry adoption and job elimination to identify workers most likely to have been affected. That approach makes it possible to study a period for which the government has no specific AI-displacement survey, but it also means the category is an estimate rather than a confirmed cause of each job loss.
The comparison draws on Goldman’s earlier work on workers displaced by technological change since the 1980s. Across that research, Goldman reported longer searches, lower real pay after reemployment and weaker earnings growth over time. In the new note, Mei described the effects as “comparable in magnitude” to earlier technology-driven displacement. The new analysis covers a much shorter period, so its findings are an early signal rather than a long-term account of AI’s labor-market effects.
Government data provide a separate measure of reemployment for laid-off workers generally, not specifically those 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 regained 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.
““comparable in magnitude””
— Pierfrancesco Mei, Goldman Sachs economist, as quoted in Fortune
How Much AI Caused the Loss
The central uncertainty is whether the jobs in Goldman’s “likely AI-displaced” group were actually lost because of AI. The measure identifies workers whose occupations and industries are exposed to AI and whose positions were eliminated; it does not confirm the employer’s reason for each layoff. No government survey directly records AI-caused job losses, and the Goldman note itself is not publicly available for independent examination.
The findings also cover only recent job losses, leaving little time to assess long-term wages, career changes or repeat unemployment for the people in the group. Mei reportedly said it was too early to evaluate effects across education and region. The source material also says Goldman expects AI-related job losses to speed up when the economy slows, but the reported early findings do not establish how a future recession would affect this group.
Tracking Reemployment and Pay
The next useful evidence will be whether the estimated gap in job-search duration persists as more workers’ outcomes are observed, and whether those who return to work regain their former pay and career footing. Longer-term follow-up could help distinguish a temporary slowdown in hiring from lasting earnings damage.
For now, readers should treat the new AI-specific figures as Goldman estimates reported by Fortune, and distinguish them from the historical findings and government data on laid-off workers generally. The analysis does not establish how many jobs AI has caused to disappear, or whether the recent pattern will continue as adoption and economic conditions change.
Key Questions
What did Goldman Sachs estimate about workers likely displaced by AI?
According to a Goldman note reported by Fortune, workers classified as likely AI-displaced since 2025 took about one month longer to find new work than other laid-off workers and were roughly 10 percentage points more likely to still be unemployed a year later.
Does the estimate confirm that AI caused these workers’ layoffs?
No. Goldman used an indirect measure based on AI exposure, industry adoption and position elimination. The source material says there is no government survey asking workers whether AI caused their job loss, so the group is described as likely AI-displaced rather than confirmed.
Why does Goldman compare the results with earlier technology layoffs?
Goldman’s historical research found that workers displaced by earlier technological changes took longer to find jobs and experienced lower real pay after reemployment. The comparison gives readers a precedent, but it does not establish that AI’s long-term effects will be identical.
Which workers appear to face a longer return to full-time work?
In the reported Goldman estimates, 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. Separate government data cited in the source material also show lower reemployment among workers aged 55 to 64 than among those aged 25 to 54.
What remains unknown about the findings?
The note is not public, the AI-displacement category is an estimate, and the observation period is short. It is not yet clear how outcomes vary by education or region, whether the reported differences will persist, or how many layoffs were directly caused by AI.
Source: ThorstenMeyerAI.com
