🔍 Read the full analysis: AI Layoffs Are Bringing Back Memories Of Earlier Technology Shocks on ThorstenMeyerAI.com
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TL;DR
A Goldman Sachs note dated Oct. 29, 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. The results echo Goldman’s public research on earlier technology-related job losses, but the new estimates rely on an indirect measure of AI displacement and have not been independently verified.
Workers likely displaced by AI have taken longer to find new jobs than other laid-off workers, according to a Goldman Sachs client note dated Oct. 29, as reported by Fortune. The bank estimates the affected workers took about a month longer to find work and were roughly 10 percentage points more likely to remain unemployed a year after losing their jobs, a pattern that resembles the lasting costs of earlier technology-related job losses.
The new figures are reported estimates, not results independently checked against a public Goldman note. The note was sent to clients and was not publicly available; Fortune business editor Nick Lichtenberg reported its findings on Oct. 30. The source material says other coverage repeated Fortune’s numbers. Goldman economist Pierfrancesco Mei described the estimated effects as comparable in magnitude to earlier waves of technological change.
Because no government survey asks whether AI caused a worker’s job loss, Goldman created a proxy measure using Labor Department data on displaced workers. It examined more than 15,000 people who lost jobs between 2016 and 2025, scoring their occupations’ exposure to AI, the pace of AI adoption in their industries and whether their positions were eliminated. Workers in the top 30% of that score were classified as “likely AI-displaced.” Goldman found no significant difference from other laid-off workers for job losses before 2023, when AI adoption began to rise, according to the report.
For losses since 2025, Fortune reported, the likely AI-displaced group took about one month longer to find new work and was around 10 percentage points more likely to still be unemployed one year later. Workers aged 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. The reported analysis also found that affected workers were more likely to leave their former occupation or industry; some who returned to work, particularly older workers, took jobs 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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The Costs Extend Beyond the Layoff
The estimates focus on what happens after a job is lost: the time needed to find another position, whether the worker returns to full-time work and what kind of work is available. A longer search can mean a longer period without wages, while a move into another highly AI-exposed role may leave a worker vulnerable to further change. The reported figures do not establish that AI alone caused each job loss, but they suggest that the disruption may be measured in more than the number of announced cuts.
Goldman’s public historical research offers a longer view. It found that workers displaced by technology experienced more than a 3% real-pay decline when reemployed and nearly 10 percentage points less real earnings growth over the following decade than workers who had not been laid off. The findings indicate that finding another job does not necessarily restore a worker’s previous earnings path. The comparisons are historical and do not prove that current AI-displaced workers will experience the same long-term outcomes.
The potential strain extends beyond individual workers. A prolonged search can affect household income and may make local labor markets slower to absorb people displaced from particular occupations. The source material also cites Goldman’s finding that displacement costs are larger during downturns, and says the bank expects AI-related job losses to accelerate if economic growth weakens. That is a forecast, not a confirmed description of current job losses.
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A Four-Decade Technology Comparison
Goldman’s comparison draws on research published before the client note. In its June 2026 “Top of Mind” report and a September summary, Mei and colleagues Jessica Rindels and David Mericle examined technology exposure across more than 300 occupations and followed workers through National Longitudinal Surveys covering more than 20,000 people. Their historical analysis found that workers displaced from technology-exposed jobs took about a month longer to find new work than people laid off from stable or growing occupations.
The same research connected technology-related job loss with lower pay and weaker earnings growth after reemployment. It also found better outcomes among workers who retrained within three years: roughly 2 percentage points more real wage growth over ten years and about a 10-point lower chance of becoming unemployed again. These are associations in Goldman’s historical data, not a guarantee that retraining will produce those results for every worker or that the same pattern will hold for AI displacement.
Government figures cited in the source material show that reemployment challenges vary by age even among laid-off workers generally. 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 returned to full-time work, about 49% earned as much as before or more, down from about 62% two years earlier, according to Bureau of Labor Statistics data cited by the source.
““comparable in magnitude””
— Pierfrancesco Mei, Goldman Sachs economist, as quoted in Fortune
How Much AI Caused the Displacement
The reported Goldman note is not public, and its figures have not been independently verified here. Its classification is an indirect estimate: the score combines occupational AI exposure, industry adoption and whether a job was eliminated. It cannot establish from those factors alone that AI caused a particular worker’s layoff. The source material does not provide the full methodology, underlying tables or uncertainty ranges for the post-2025 results.
The sample period also limits what can be concluded. The reported findings cover job losses since 2025, leaving little time to observe workers’ longer-term earnings, career paths or repeated unemployment. Mei said it was too early to assess outcomes across dimensions such as education and region. It is also unclear from the available material how representative the people classified as likely AI-displaced are of all workers affected by AI, or how the results might change as employers’ adoption develops.
Longer-Term Outcomes Need Tracking
The next test is whether the reported job-search gap persists as more workers are followed over time. Researchers and labor agencies will need better evidence on whether a position was eliminated because of AI, whether affected workers return to comparable roles, and how their pay and employment stability change after reemployment. Goldman’s published historical work points to retraining as one factor associated with better outcomes, but the current note does not show that a specific training program has been tested for this group.
For now, the findings should be read as an early estimate that raises questions about the duration and cost of AI-related displacement, not as a complete account of AI’s effect on employment. A downturn could alter the pace and consequences of job losses, but the source describes that as a Goldman expectation rather than an observed result. More public detail about the note, follow-up data and clearer measures of AI-caused job loss would help establish how closely today’s experience matches earlier technology shocks.
Key Questions
What did Goldman Sachs find about workers likely displaced by AI?
According to Fortune’s report on an Oct. 29 Goldman client note, workers classified as likely AI-displaced since 2025 took about one 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.
Does the analysis prove AI caused these workers’ layoffs?
No. Goldman used a proxy based on occupational AI exposure, industry adoption and whether a position was eliminated. The method estimates which workers were likely displaced by AI; it does not confirm the cause of each individual job loss.
Are the new Goldman figures publicly available?
The source material says the note was sent to clients and was not public. The figures are reported through Fortune’s account of the note and should be treated as reported estimates rather than independently verified results.
What does Goldman’s earlier research say about technology layoffs?
Goldman’s public historical research found that workers displaced by technology took about a month longer to find work, lost more than 3% in real pay when reemployed and had nearly 10 percentage points less real earnings growth over the next decade than workers who had not been laid off.
What remains unknown about AI-related job losses?
The scale of AI-caused job loss, the long-term effects on earnings and whether outcomes differ by education or region remain unclear. The reported analysis covers a relatively recent period and uses an indirect measure of AI displacement.
Source: ThorstenMeyerAI.com
