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TL;DR
A Goldman Sachs client note, reported by Fortune on Oct. 30, estimates that workers who likely lost jobs to AI 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. The estimates are not a direct count of AI-caused layoffs, and the private note has not been independently reviewed; Goldman’s published historical research finds technology-related job losses have been linked to lasting pay and earnings penalties.
Workers estimated to have lost jobs to 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 Goldman Sachs client note reported by Fortune. The figures suggest that the cost of AI-related job loss may extend beyond the initial layoff, but they are estimates based on an occupational exposure measure, not a government count of confirmed AI-caused dismissals.
The note, dated Oct. 29, was written by Goldman economist Pierfrancesco Mei and was not publicly available. Fortune business editor Nick Lichtenberg reported its findings the following day, quoting the note. The figures for recent AI displacement in this article come from that reporting and have not been independently checked against the underlying note.
As Fortune described the method, Goldman used Labor Department data on more than 15,000 people who lost jobs between 2016 and 2025. It combined occupation-level AI exposure, industry adoption of AI and whether a position was eliminated to identify the top 30% of cases as “likely AI-displaced.” The researchers found no significant difference between that group and other laid-off workers for job losses before 2023, Fortune reported.
For workers who lost jobs since 2025, the note found a longer return to work and a greater chance of still being unemployed after a year. It also reported age differences: people aged 35 and older took about five weeks longer than comparable laid-off workers to return to full-time work, while those under 35 took about three weeks longer. The note found that displaced workers were more likely to change occupations or industries, though some who returned to work 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 Cost Can Outlast the Layoff
The findings shift attention from how many jobs are cut to what happens to workers afterward: how long they are out of work, whether they return to full-time employment and what they earn. Those outcomes matter to households and to employers weighing whether automation gains are accompanied by longer spells of unemployment or weaker job prospects for displaced staff.
Goldman’s public historical research suggests the effects may persist. Its analysis of earlier technology-related job losses found workers took about one month longer to find another job and lost more than 3% in real pay when reemployed. Over the following decade, their real earnings grew nearly 10 percentage points less than those of workers who had not been laid off, according to the research summarized in the source material. Those are historical associations, not a guarantee that current AI-displaced workers will experience the same outcomes.
The note also points to a possible difference in exposure by age. Government data cited in the source material show that among long-tenured workers aged 25 to 54 who had lost jobs, 72.9% were working again by January 2026, compared with 57.3% of those aged 55 to 64. That broader labor-market comparison is not specific to AI displacement, but it illustrates why the reported age gap deserves attention.
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Four Decades of Technology Displacement
Goldman’s comparison draws on research it has published publicly, including a June 2026 “Top of Mind” report and a September summary by Mei and colleagues Jessica Rindels and David Mericle. That work examined more than 300 occupations and followed workers over time using National Longitudinal Surveys covering more than 20,000 people.
In that historical analysis, workers displaced from occupations exposed to technological change experienced longer job searches and lower real pay after reemployment than workers laid off from stable or growing occupations. Goldman also reported that 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. These results describe past technology shifts; they do not establish that retraining will produce the same gains for every worker affected by AI today.
There is no government survey that asks displaced workers whether AI caused their job loss, according to the source material. Goldman’s recent estimate therefore relies on a combination of indicators rather than workers’ reported reasons for dismissal. The method can identify cases that appear more exposed to AI, but cannot establish that AI was the direct cause of each job cut.
““comparable in magnitude””
— Pierfrancesco Mei, Goldman Sachs economist, as quoted in Fortune
How Much AI Caused the Losses
The Goldman client note is not public, so its full methodology, caveats and tables cannot be assessed directly from the source material. The recent figures are reported by Fortune, which quoted the note; the note itself has not been independently reviewed here.
Most importantly, the “likely AI-displaced” group is an estimate. The Labor Department survey does not ask whether AI caused someone’s job loss, and the Goldman method combines occupation exposure, industry adoption and position elimination. That approach cannot separate AI from other reasons for layoffs in every case. The reported comparison also does not establish that AI alone caused the longer job searches or unemployment outcomes.
The data cover a relatively early period of AI adoption. Mei said it was too early to assess effects across dimensions including education and region. The source material also says Goldman expects AI-related job losses to accelerate when the economy slows, but does not provide a timetable or a specific forecast in the excerpts supplied. Whether a downturn will occur, and how it would affect these workers, remains uncertain.
More Evidence as AI Adoption Grows
The next useful test will be whether longer searches and weaker reemployment outcomes persist as more workers are displaced and the data period expands. Researchers and policymakers will also need better ways to distinguish AI-related job losses from layoffs caused by other business changes, and to compare outcomes by age, education, region and occupation.
Goldman’s published historical work suggests retraining may be associated with better long-term wage and employment outcomes, but the recent note does not show whether a particular training program will help workers displaced by AI. For now, the reported figures offer an early estimate rather than a settled account of AI’s labor-market effects.
Key Questions
What did Goldman Sachs report about workers displaced by AI?
According to the client note reported by Fortune, workers identified as likely AI-displaced since 2025 took about a 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 estimate prove AI caused these layoffs?
No. The estimate uses occupation exposure, industry adoption and position elimination to identify likely cases. The government survey used does not ask workers whether AI caused their job loss, so the method cannot confirm the cause of each layoff.
Why are older workers highlighted?
The note, as reported by Fortune, found workers aged 35 and older took about five weeks longer than comparable laid-off workers to return to full-time work; workers under 35 took about three weeks longer. The report does not establish why that age difference occurred.
What does Goldman’s historical research say about retraining?
Goldman’s historical analysis found that 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. The findings concern past displacement and do not guarantee the same results for current workers.
Source: ThorstenMeyerAI.com
