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TL;DR
A Goldman Sachs client note, as 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. Goldman’s published research on earlier technology-related layoffs finds longer searches and lasting wage effects, but the new estimate is based on an indirect measure and remains preliminary.
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 findings from a Goldman Sachs client note reported by Fortune. The comparison echoes Goldman’s research on earlier technology-related layoffs, which found that job-search and pay effects could persist long after workers were rehired.
The new note was written by Goldman economist Pierfrancesco Mei and dated October 29. The note is not public; the figures were reported by Fortune the following day, which quoted it. The source article says other outlets repeated Fortune’s figures, so the new results should be treated as reported estimates, not independently verified findings.
Goldman did not identify AI displacement through a direct survey question. It analyzed Labor Department survey data on more than 15,000 people who lost jobs between 2016 and 2025, combining estimated occupational AI exposure, industry adoption and whether a position was eliminated. The top 30% of its resulting measure were classified as “likely AI-displaced.” Goldman found no significant difference in outcomes between this group and other laid-off workers for job losses before 2023, according to the report.
For workers losing jobs since 2025, the reported note found a longer return to work and a higher chance of unemployment one year later. Workers aged 35 and older took about five weeks longer to return to full-time work than comparable laid-off workers; for those under 35, the reported gap was about three weeks. The analysis also found that AI-displaced workers were more likely to leave their previous occupation or industry, while some rehired workers moved into 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 Can Outlast the Layoff
The findings shift attention from the number of announced cuts to what happens to workers afterward: how long they remain unemployed, whether they regain full-time work and what they earn once rehired. Those outcomes affect household income and can shape workers’ careers well beyond the date their previous job ends.
Goldman’s public historical research gives the reported AI estimates a longer-term comparison, though it does not prove that every AI-related layoff will follow the same path. In that research, workers displaced by technology took about a month longer to find new work, lost more than 3% in real pay when rehired and experienced nearly 10 percentage points less real earnings growth over the next decade than workers who were never laid off. These are historical findings, not a forecast for every current worker.
The reported age differences also point to uneven exposure to the costs. Separate government figures cited in the source show that 72.9% of long-tenured workers aged 25 to 54 were working again by January 2026, compared with 57.3% of those aged 55 to 64. That comparison covers long-tenured displaced workers generally, not a group identified as displaced by AI, and should not be read as an AI-specific result.
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Four Decades of Displacement Data
Goldman’s comparison draws on its public research, including a June 2026 “Top of Mind” report and a September summary by Mei and colleagues Jessica Rindels and David Mericle. They examined more than 300 occupations and used National Longitudinal Surveys that have followed over 20,000 workers through their careers. The research tracked people in occupations exposed to technology across decades, then compared their outcomes with those of workers laid off from stable or growing occupations.
That historical work found that retraining was associated with better outcomes: technology-displaced workers who retrained within three years had about two percentage points more real wage growth over the following decade and a roughly 10-point lower chance of becoming unemployed again. The source does not establish that retraining alone caused those differences.
The pay picture for displaced workers has also weakened in recent years. Bureau of Labor Statistics figures cited in the source show that about 49% of long-tenured workers who returned to full-time work earned at least as much as before, down from about 62% two years earlier. This is a broad measure of displaced workers, not a separate count of people laid off because of AI.
““comparable in magnitude””
— Pierfrancesco Mei, Goldman Sachs economist, as quoted in Fortune
How AI Displacement Is Identified
The central limitation is that the Labor Department survey does not ask whether AI caused a person’s job loss. Goldman’s “likely AI-displaced” category is an estimate based on exposure, industry adoption and job elimination, not a direct confirmation from workers or employers. The source article says the note itself is unavailable publicly, and its findings cannot be checked against the full methodology from the note.
The reported results cover early job losses since 2025 and may not represent the effects of AI across all occupations or regions. Mei said it was too early to assess outcomes by education and location. It is also unclear from the available material how much of each job loss was caused by AI rather than other business or economic factors, and whether the reported differences will persist as more workers are tracked.
Longer-Term Outcomes Need Tracking
The next test is whether the early job-search gap remains as more data become available and whether workers who return to work recover their previous pay. Further results broken out by age, education, region and occupation would help clarify who faces the greatest difficulty and which kinds of jobs are available after displacement.
Goldman’s historical analysis suggests retraining is associated with better later employment and wage outcomes, but the supplied research does not establish a guaranteed result for any worker or program. For now, the reported note offers an early comparison, while the longer-term consequences of AI-related layoffs—and how much of them can be attributed specifically to AI—remain unsettled.
Key Questions
What did Goldman Sachs find about workers likely displaced by AI?
According to a client note reported by Fortune, workers 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.
How did Goldman identify likely AI-related job losses?
It combined estimated occupational AI exposure, how quickly an industry was adopting AI and whether a position was eliminated. The Labor Department survey used in the analysis does not directly ask whether AI caused a layoff, so the category is an estimate rather than a confirmed count.
Do the new findings show that AI caused every job loss in the group?
No. The method identifies workers whose occupations and industries score highly on measures related to AI exposure and adoption. The available reporting does not establish that AI was the sole cause of each person’s job loss.
Goldman’s published research found that workers displaced by technology lost more than 3% in real pay when they found new work and had nearly 10 percentage points less real earnings growth over the following decade than workers who were never laid off.
What remains unknown about AI-related layoffs?
The full Goldman client note is not public, and the reported estimate relies on an indirect measure of AI displacement. Longer-term outcomes and differences by education, region and occupation are not yet clear.
Source: ThorstenMeyerAI.com
