🔍 Read the full analysis: The Aftermath Of AI Layoffs, Seen Through Four Decades Of Tech Change on ThorstenMeyerAI.com
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TL;DR
Goldman Sachs estimated that workers likely displaced by AI since 2025 took about a month longer to find work than other laid-off workers and were roughly 10 percentage points more likely to remain unemployed a year later, according to Fortune’s report of a private client note. The findings echo Goldman’s public research on earlier technology-related job losses, which found lasting pay and employment costs; the new estimate is not a direct count of confirmed AI layoffs.
Workers Goldman Sachs classifies as likely displaced by AI since 2025 took about a month longer to find new work than other laid-off workers and were roughly 10 percentage points more likely to remain unemployed a year later, according to a private Goldman client note described by Fortune. The estimate suggests the impact of AI-related job losses may extend beyond the initial layoff, though the group is based on an indirect measure rather than confirmed individual reports of AI causing job loss.
The note, dated October 29, 2026, was not publicly available. Fortune business editor Nick Lichtenberg reported its findings the next day, quoting the note; the figures here are therefore reported findings, not independently verified from the document. Goldman economist Pierfrancesco Mei compared workers it judged likely to have been displaced by AI with other people who had lost jobs.
Because government surveys do not ask whether AI caused a worker’s job loss, Goldman constructed a measure using Labor Department data on displaced workers. According to Fortune’s account, Goldman examined more than 15,000 people who lost jobs from 2016 through 2025, scoring their circumstances by occupational exposure to AI, industry adoption and whether a position was eliminated. People in the top 30% of that score were designated “likely AI-displaced.” Goldman found no significant difference from other laid-off workers for job losses before 2023, Fortune reported.
For job losses since 2025, the note reportedly found longer searches and a greater chance of remaining out of work after a year. It also reported an age difference: workers 35 and older took about five weeks longer than comparable laid-off workers to return to full-time employment, while workers under 35 took about three weeks longer. The group was also more likely to leave its previous occupation or industry, but some re-employed workers 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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The Cost Extends Beyond the Layoff
The findings focus attention on what happens after a job disappears: how quickly a worker is rehired, what the next job pays and whether employment lasts. If the reported pattern holds, workers affected by AI may face costs that are not captured by a layoff tally alone. Longer searches can mean more time without wages, while a move to another occupation may require new skills or bring different pay and working conditions.
Goldman’s public historical research offers a longer view, but it is not proof that every AI-related layoff will produce the same outcome. That research found technology-displaced workers took about one month longer to find work and lost more than 3% in real pay when rehired. Over the following decade, their real earnings growth was nearly 10 percentage points lower than that of workers who had not been laid off. The comparison makes the new estimates relevant to workers and employers, while the distinction between historical evidence and a recent, modeled AI group remains important.
The results also point to uneven exposure. The reported longer return to full-time work among older workers suggests age may shape recovery, although the note’s reported figures do not explain the reasons for the difference. A broad measure of likely displacement cannot establish how much of the gap comes from AI itself, occupation, industry or other factors.
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Four Decades of Technology Displacement
The new estimate is set against research Goldman published publicly in a June 2026 “Top of Mind” report and a September summary. Mei, Jessica Rindels and David Mericle tracked workers across more than 300 occupations, using National Longitudinal Surveys that have followed more than 20,000 people through their careers. The researchers compared workers in occupations more exposed to technological change with others over several decades.
That historical work found technology-displaced workers had a slower return to work, a real-pay loss of more than 3% after reemployment and nearly 10 percentage points less real earnings growth over the next decade than workers who were never laid off. It also found that retraining within three years was associated with about two percentage points more real wage growth over ten years and a roughly 10-point lower chance of becoming unemployed again. These are historical associations, not guarantees that retraining will produce the same results for workers displaced by AI today.
Government data provide a separate view of age and reemployment among long-tenured workers who lost jobs, regardless of the stated cause. By January 2026, 72.9% of those aged 25 to 54 were working again, compared with 57.3% of those aged 55 to 64. Bureau of Labor Statistics data cited in the source material also show that 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. Those figures cover laid-off workers generally, not a confirmed AI-displaced group.
““comparable in magnitude””
— Pierfrancesco Mei, Goldman Sachs economist, as quoted in Fortune’s report of the client note
How Many Jobs AI Actually Displaced
The estimate does not identify workers who individually confirmed that AI caused their job loss. It classifies people using a combination of occupation exposure, industry adoption and job elimination, so its “likely AI-displaced” category is an analytical proxy. The underlying client note is not public, and Fortune’s account is the cited basis for its figures.
It is also too early, according to Mei’s reported wording, to assess effects across education, region and other dimensions. The available material does not establish how the results vary across those groups, whether workers’ new roles will last, or how pay changes for the AI-exposed cohort as it ages. Goldman’s historical findings and government statistics concern broader worker groups and should not be treated as direct confirmation of the new estimate.
Evidence to Watch in Future Data
The next test will be whether additional labor-market data and research show that workers in AI-exposed roles continue to face longer searches, lower reemployment rates or pay losses. A direct government measure identifying whether AI caused a layoff would help distinguish AI displacement from other reasons for job loss; the source material says no such survey question currently exists.
Goldman also expects AI-related job losses to accelerate if economic growth slows, according to the source material, and finds that technology displacement costs have been larger in downturns. That is a forecast, not a confirmed outcome. For now, the reported comparison adds an early warning about possible adjustment costs, while the size and durability of AI’s effect on employment remain unsettled.
Key Questions
What did Goldman Sachs find about workers likely displaced by AI?
According to Fortune’s report of a private Goldman client note, workers in the group took about one month longer to find new work and were roughly 10 percentage points more likely than other laid-off workers to remain unemployed a year later.
Does the estimate count confirmed AI-related layoffs?
No. Goldman reportedly used a scoring method based on occupation exposure to AI, industry adoption and whether the position was eliminated. “Likely AI-displaced” is an estimated category, not a count based on workers confirming AI caused their layoff.
Which workers reportedly had the longest return to full-time work?
In the reported Goldman findings, 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.
What did earlier technology layoffs do to workers’ pay?
Goldman’s public historical research found technology-displaced workers lost more than 3% in real pay when rehired and had nearly 10 percentage points less real earnings growth over the following decade than workers who were never laid off. Those historical results do not guarantee the same outcome for people affected by AI.
Is the Goldman client note publicly available?
The source material says the note was sent to clients and was not public. The reported findings are attributed to Fortune’s account of the note.
Source: ThorstenMeyerAI.com
