AI Layoffs And 40 Years Of Tech Shocks: What Goldman Sachs Is Seeing

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Goldman Sachs 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 roughly 10 percentage points more likely to remain unemployed a year later, according to a client note reported by Fortune. The analysis matters because it suggests AI-linked job losses may carry costs beyond the initial layoff, although Goldman’s method identifies likely cases rather than confirming that AI caused each loss.

The findings come from a Goldman note dated October 29, 2026, by economist Pierfrancesco Mei. Goldman’s client note is not public; the figures here are based on Fortune’s October 30 account, which quoted the note. The figures have not been independently verified against the original analysis.

Because government surveys do not ask laid-off workers whether AI caused their job loss, Goldman constructed a proxy using Labor Department data on people who lost jobs between 2016 and 2025. It combined occupation-level AI exposure, industry adoption and whether a position was eliminated. Workers in the top 30% of its resulting measure were classified as “likely AI-displaced.” Goldman reportedly found no significant difference from other laid-off workers for job losses before 2023, when AI adoption began to rise.

For workers in the likely-displaced group who lost jobs since 2025, the reported estimates point to a longer search and a tougher return to work. Workers aged 35 and older took about five weeks longer than comparable laid-off workers to return to full-time jobs, while those under 35 took about three weeks longer. Goldman also reported that AI-displaced workers were more likely to leave their previous occupation and industry, but some who found new jobs moved into roles with similar or higher AI exposure.

The Cost Can Outlast the Layoff

The reported findings shift attention from the number of jobs cut to how quickly displaced workers find another job, what they earn and whether they remain employed. A longer job search can mean lost income and greater financial strain; a return to work in a similarly exposed occupation may leave workers vulnerable to further disruption. The Goldman estimates describe associations, however, and do not establish that AI alone caused the layoffs or later employment outcomes.

Goldman’s public research on earlier technology-related displacement offers a longer historical comparison. It found that workers displaced by technology took about one month longer to find work, earned more than 3% less in real terms when rehired, and experienced nearly 10 percentage points less real earnings growth over the following decade than workers who were never laid off. Those historical results do not prove that AI-displaced workers will follow the same path, but they underline why tracking post-layoff wages and job stability matters.

Age and the state of the economy may affect how difficult the return is. Government figures cited in the source material 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. Those figures cover long-tenured displaced workers generally, not people identified as AI-displaced.

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Four Decades of Displacement Data

Goldman’s historical comparison draws on its publicly available research, including a 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 following over 20,000 workers through their careers. They compared people in occupations most exposed to technology in each decade with other workers.

The historical analysis reported that technology-displaced workers lost more than 3% in real pay when they found new work, compared with negligible losses for workers laid off from stable or growing occupations. Their real earnings growth over the next decade was nearly 10 percentage points lower than for people who had not been laid off. These results concern earlier technology waves and should not be treated as observed long-term outcomes for workers displaced by AI since 2025.

Goldman’s research also linked retraining with better outcomes in its historical data. Workers displaced by technology who retrained within three years had about 2 percentage points more real wage growth over the next decade and a roughly 10-point lower chance of becoming unemployed again. This is an association in the analysis, not proof that retraining alone caused the difference.

““comparable in magnitude””

— Pierfrancesco Mei, Goldman Sachs economist, as quoted in Fortune

AI Causation Remains Hard to Measure

The new estimates are not a count of confirmed AI-caused layoffs. The government survey used in the analysis does not ask whether AI cost someone a job, so Goldman relied on a constructed score combining exposure, adoption and position elimination. That proxy can identify workers considered likely to have been displaced by AI, but it cannot establish the cause of every job loss.

The original Goldman note is not public, and the reported figures come from Fortune’s account. The analysis also covers a relatively recent period, leaving little time to observe longer-term earnings, job stability or repeat unemployment. Goldman reportedly said it is too early to assess outcomes by education and region. It is also unclear how the estimates may change as more data become available or how much of the difference reflects AI rather than other conditions affecting hiring.

More Follow-Up Data Needed

The next useful evidence will come as researchers can follow workers who lost jobs since 2025 for longer. That would help show whether the reported gaps in job-search duration and unemployment persist, and whether workers who return to employment regain their former pay. Breakdowns by age, education and region could clarify which groups face the greatest difficulties.

Goldman’s historical findings suggest retraining is worth tracking, but the reported association does not settle which programs help or who can access them. For now, the client note provides an early estimate rather than a definitive measure of AI’s employment effects. Further analysis and longer follow-up will be needed to distinguish AI-related displacement from wider changes in the labor market.

Key Questions

What did Goldman Sachs report about AI-linked layoffs?

According to Fortune’s report on a Goldman client note, workers classified as likely displaced by AI since 2025 took about one 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.

Does Goldman know which workers lost jobs because of AI?

Not directly. The government survey used does not ask whether AI caused a job loss. Goldman created a proxy measure using occupation exposure, industry AI adoption and whether a position was eliminated, so the results identify workers considered likely to have been displaced.

What does Goldman’s historical research say about technology layoffs?

Goldman’s public research found that workers displaced by earlier technology waves took longer to find work, lost more than 3% in real pay when rehired and had weaker real earnings growth over the following decade than workers who were never laid off.

Which workers appear to face longer job searches?

In the reported AI analysis, workers aged 35 and older took about five weeks longer than comparable laid-off workers to return to full-time employment; workers under 35 took about three weeks longer. These are reported estimates, not confirmed outcomes for every worker.

Is retraining proven to prevent the long-term effects?

No. Goldman’s historical data linked retraining within three years to better wage growth and a lower chance of unemployment again, but that association does not prove retraining caused the improved outcomes or establish which programs are most effective.

Source: ThorstenMeyerAI.com