🔍 Read the full analysis: Will AI Layoffs Leave Lasting Scars? Goldman Sachs Looks To Tech History 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 new jobs than other laid-off workers and were about 10 percentage points more likely to remain unemployed a year later. Goldman’s public research on earlier technology-related job losses finds longer job searches and weaker wage growth, but the AI-specific estimates are based on an indirect measure and remain preliminary.
Goldman Sachs estimates that workers likely displaced by AI since 2025 have taken 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 later, according to a client note reported by Fortune. The analysis matters because Goldman’s research on earlier technology-related job losses finds that the costs can extend beyond the initial layoff into job searches, pay and later employment.
The client note was dated October 29, 2026, and its details are not publicly available. The figures were reported by Fortune the following day, based on the note; they should be treated as reported findings, not independently verified estimates. Goldman economist Pierfrancesco Mei compared workers the bank classified as likely AI-displaced with other people who had lost jobs.
Because government surveys do not ask whether AI caused a job loss, Goldman constructed an estimate using Labor Department data on displaced workers. As described in the report, the bank assessed more than 15,000 people who lost jobs between 2016 and 2025, combining occupational exposure to AI, industry adoption and whether the position had been eliminated. It counted the highest-scoring 30% 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 the post-2025 group, Fortune reported a longer route back to full-time work among older workers: those aged 35 and above took about five weeks longer than comparable laid-off workers, while those under 35 took about three weeks longer. The report also says AI-displaced workers were more likely to leave their former occupation and industry. Some who found work moved into jobs with similar or higher AI exposure, particularly older workers.
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 Can Outlast the Layoff
The analysis shifts attention from the number of jobs cut to what happens to workers afterward. A longer search can mean more time without wages, while a lower-paid next job can affect household finances well after someone is reemployed. Goldman’s public historical research suggests these effects may accumulate: workers displaced by technology took about one month longer to find a new job, lost more than 3% in real pay on reemployment, and had nearly 10 percentage points less real earnings growth over the following decade than workers who had not been laid off.
The effects are not evenly distributed. Older workers in the reported AI analysis took longer to return to full-time work, and government figures for long-tenured displaced workers show a similar age difference. That does not prove AI caused the difference, but it underlines why the quality and durability of a replacement job matter alongside the initial layoff count.
Goldman’s historical analysis also links retraining with better outcomes: 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. Those are associations in historical data, not a guarantee that training will produce the same results for current workers.
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Four Decades of Technology Displacement
Goldman’s comparison draws on public research published in its June 2026 Top of Mind report and a September summary. Mei, Jessica Rindels and David Mericle examined more than 300 occupations over several decades, identifying occupations most exposed to technology in each period and tracking workers through the National Longitudinal Surveys, which have followed more than 20,000 people over their careers.
That historical work provides a basis for comparing long-term outcomes, but it is distinct from the newer AI estimate. The older research follows technology-related displacement over time; the new client note uses an indirect score to identify likely AI-related job losses. The two analyses therefore do not establish that every worker in the newer group lost a job because of AI, or that past outcomes will repeat exactly.
Government data also show that recovery after layoffs can vary by age and time. For long-tenured workers aged 25 to 54, 72.9% were working again by January 2026, 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 or more than before, down from about 62% two years earlier. These figures cover laid-off workers generally, not people identified as displaced by AI.
““comparable in magnitude””
— Pierfrancesco Mei, Goldman Sachs economist, as quoted in Fortune
Limits of the AI Job Estimates
The AI-specific numbers rely on Goldman’s model rather than a government measure that asks workers whether AI caused their job loss. The client note is not public, and the reported estimates have not been independently confirmed here. The score combines occupation-level AI exposure, industry adoption and job elimination, which can indicate possible displacement but cannot establish the cause of each individual layoff.
The available account also does not provide enough detail to judge the estimates’ full statistical uncertainty or how outcomes differ across regions, education levels and industries. Goldman’s economist said it was too early to assess some of those dimensions. It is also unclear whether the reported post-2025 pattern will persist as AI adoption and labor-market conditions change.
Goldman expects displacement costs to be greater in an economic downturn and its economists anticipate AI-related job losses could accelerate if growth slows. That is a forecast, not a confirmed outcome. The source material does not specify how many layoffs were directly caused by AI or provide a complete count of affected workers.
Tracking Reemployment and Pay
The next evidence will come from follow-up data on whether workers identified as likely AI-displaced return to work, how long their searches last, and whether their next jobs match their previous pay and occupation. Comparisons across age, education and region would help establish which workers face the greatest barriers. For now, the reported note offers an early estimate, while Goldman’s historical research provides a longer-term reference point rather than a firm forecast for AI’s effects.
Labor Department data will also help show whether broader layoff and reemployment patterns are changing. A slowing economy could make it harder to separate the effects of AI adoption from weaker hiring. Until more direct measures are available, the causes of individual job losses and the durability of the reported AI-related gap remain uncertain.
Key Questions
What did Goldman Sachs report about workers likely displaced by AI?
According to Fortune’s account of a Goldman client note, workers classified as likely AI-displaced since 2025 took about one month longer to find work and were roughly 10 percentage points more likely to remain unemployed a year later than other laid-off workers.
How did Goldman identify likely AI-related job losses?
Goldman reportedly combined occupational exposure to AI, the pace of AI adoption in an industry and whether a position was eliminated. It classified the highest-scoring 30% as likely AI-displaced. This is an estimate, not direct confirmation of why each person lost a job.
Does the analysis show that AI caused every job loss in the group?
No. The analysis uses an indirect scoring method because government surveys do not ask whether AI caused a worker’s layoff. It identifies workers considered likely to have been displaced, but does not establish the cause of every individual job loss.
What does Goldman’s historical research say about technology layoffs?
Goldman’s public research found that workers displaced by technology took about a month longer to find work, lost more than 3% in real pay upon reemployment and saw weaker real earnings growth over the following decade than workers who had not been laid off.
What remains unknown about the AI findings?
The client note is not public, and Fortune’s reported figures have not been independently verified here. The effects by education and region, the number of layoffs directly caused by AI, and whether the reported differences will persist are not yet clear.
Source: ThorstenMeyerAI.com
