🔍 Read the full analysis: The Worker Fallout From AI Layoffs, Compared With Past Tech Shocks on ThorstenMeyerAI.com
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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 new jobs than other laid-off workers and were more likely to remain unemployed a year later. Goldman’s public research on earlier technology-related job losses finds slower reemployment, lower real pay and weaker earnings growth over time. The new estimates are indirect, and the client note is not public.
Workers likely displaced by AI since 2025 took 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 new Goldman Sachs estimate reported by Fortune. The findings suggest the costs of AI layoffs may resemble those seen after earlier technology shocks, when workers faced prolonged job searches and weaker pay; the underlying client note is not public.
Goldman economist Pierfrancesco Mei compared recent laid-off workers with people affected by earlier technological change. Fortune reported the note’s findings on October 30, a day after its October 29 publication. Goldman did not publish the note publicly, so the recent figures are reported estimates, not independently reviewable results.
Because government surveys do not ask whether AI caused a person’s job loss, Goldman developed a proxy. It analyzed more than 15,000 people who lost jobs from 2016 to 2025, combining occupational exposure to AI, the pace of AI adoption in the industry and whether the position was eliminated. Workers in the top 30% of its score were classified as “likely AI-displaced.” Goldman reportedly found no significant difference between that group and other displaced workers for job losses before 2023.
For job losses since 2025, the reported estimates point to a longer recovery, with effects that differ by age. Workers aged 35 and older took about five weeks longer to return to full-time work than comparable laid-off workers; those under 35 took about three weeks longer. Fortune also reported that AI-displaced workers were more likely to leave their former occupation or industry, while some who found jobs 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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Long Searches Can Mean Lasting Losses
The immediate layoff count captures only part of the economic effect. A longer search can mean months without a paycheck, while a lower-paid next job can compound the cost over years. Goldman’s public historical research found that workers displaced by technology took about a month longer to find work and lost more than 3% in real pay when reemployed. Their real earnings grew nearly 10 percentage points less over the following decade than earnings for workers who were never laid off.
The findings matter to workers weighing retraining, employers making automation decisions and policymakers considering support for displaced workers. In Goldman’s historical data, 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. Those are associations in historical data, not a guarantee that retraining will produce the same result for every worker affected by AI.
Age and the broader economy may shape how severe the fallout becomes. Government figures cited in the source show 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. Goldman’s historical analysis also found larger displacement costs during downturns, leaving the outlook more uncertain if economic conditions weaken.
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Four Decades of Technology Displacement
The recent comparison draws on Goldman research published in its June 2026 “Top of Mind” report and a September summary. Mei and colleagues Jessica Rindels and David Mericle examined more than 300 occupations and used National Longitudinal Surveys tracking over 20,000 workers to follow employment outcomes across careers. They identified occupations most exposed to technology in each decade and studied what happened to workers who held those jobs.
That historical work found that workers displaced by technology were slower to regain work, took a real-pay hit on reemployment and recorded weaker earnings growth over the next decade. The new note applies a different method to a much more recent period, using an estimate of AI exposure rather than a direct survey answer about why a worker lost a job. The two bodies of evidence offer a comparison, but they do not establish that AI caused each recent layoff.
Other figures in the source indicate pressure on reemployed workers’ pay. 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 the Bureau of Labor Statistics figures cited in the source. That measure covers long-tenured workers generally, not only people classified as likely displaced by AI.
““comparable in magnitude””
— Pierfrancesco Mei, Goldman Sachs economist, as quoted in Fortune
AI Layoff Counts Remain Estimated
The central limitation is that the United States has no government survey identifying AI as the cause of an individual layoff. Goldman’s “likely AI-displaced” category relies on a score combining exposure, industry adoption and job elimination; it does not confirm that AI caused a specific worker’s job loss. The latest estimates also cover a short period and come from a client note that Fortune reported, rather than a publicly available report that readers can inspect.
It is not yet clear how outcomes vary by education, region or other worker characteristics, or whether the recent patterns will persist as AI adoption changes. The source also does not establish that every worker who moves into a role with high AI exposure faces the same risk, nor does it isolate AI as the cause of the broader pay figures reported for long-tenured workers.
Longer Follow-Up Will Test the Pattern
The next test will be whether the early job-search gap appears in later data and whether it translates into lasting differences in employment and pay. The reported Goldman figures cover workers displaced since 2025; longer follow-up is needed to compare their outcomes over several years with the historical pattern.
Readers and policymakers will also need more direct evidence on why jobs are eliminated. Until surveys or other data can distinguish AI-related losses from other layoffs, estimates will depend on proxies such as Goldman’s. The economic outlook matters too: Goldman’s historical findings suggest layoffs can carry higher costs in downturns, but the source does not quantify how a future recession would affect this particular group.
Key Questions
What did Goldman Sachs estimate about workers displaced by AI?
According to Fortune’s account of a Goldman client note, workers classified as likely AI-displaced since 2025 took about a 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 scored job losses using occupational AI exposure, industry adoption and whether a position was eliminated. The top 30% were classified as likely AI-displaced. This is an estimate, not confirmation that AI caused any individual layoff.
What do past technology layoffs suggest?
Goldman’s public historical research found that technology-displaced workers took longer to find jobs, lost more than 3% in real pay when reemployed and had weaker real earnings growth over the following decade than workers who were never laid off.
Are older workers having a harder time returning to work?
The reported Goldman estimate says workers aged 35 and older took about five weeks longer to return to full-time work, compared with about three weeks for workers under 35. Separate government figures cited in the source also show lower reemployment among workers aged 55 to 64 than among those aged 25 to 54.
Does the research show that retraining prevents job losses?
No. In Goldman’s historical data, workers who retrained within three years had better later wage growth and a lower chance of becoming unemployed again. That is an association in historical data, not proof that retraining caused the improvement or guarantees the same outcome for workers displaced by AI.
Source: ThorstenMeyerAI.com
