How Workers Fare After AI Layoffs: A Look Back At Four Decades Of Tech Shocks

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A Goldman Sachs estimate reported by Fortune says workers 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 still be unemployed a year later. The findings put early AI-related job losses alongside four decades of technology-driven displacement, but the estimate is indirect and the Goldman note is not publicly available.

Goldman economist Pierfrancesco Mei based the new analysis on the Labor Department’s Displaced Worker Supplement to the Current Population Survey, according to Fortune’s October 30 report. The government survey does not ask respondents whether AI caused their job loss. Goldman instead assessed more than 15,000 workers who lost jobs between 2016 and 2025, combining occupational exposure to AI, the pace of AI adoption in each industry, and whether the position was eliminated. Workers in the highest-scoring 30% were classified as “likely AI-displaced.”

Fortune reports that, for job losses since 2025, this group took about a month longer to find another job and was roughly 10 percentage points more likely to remain unemployed one year later than other displaced workers. Workers 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. These figures come from Fortune’s account of a client note that has not been released publicly, so they cannot be checked directly against the full analysis.

Goldman’s publicly available historical research offers a longer comparison. It finds that workers displaced by technology took about a month longer to find work, earned more than 3% less in real pay when reemployed, and experienced nearly 10 percentage points less real earnings growth over the following decade than workers who were not laid off. In that historical analysis, workers who retrained within three years had about two percentage points more real wage growth over ten years and a roughly 10-point lower chance of becoming unemployed again. These are historical associations, not a guarantee that retraining will produce the same outcomes for workers displaced by AI today.

The Costs Continue After Layoffs

Layoff totals capture only the initial loss. The Goldman estimate points to a longer period without work for people whose jobs may have been affected by AI, while the historical findings indicate that returning to employment may not restore lost earnings. The distinction matters to workers and their households: the time spent searching and the pay and security of the next job shape the financial impact beyond the day employment ends.

The age differences reported in the new note also suggest that the effects may not be evenly shared. Separately, Bureau of Labor Statistics figures cited in the source material show that among 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. Those figures cover laid-off workers generally, not people identified as AI-displaced, so they provide context rather than a direct measure of AI’s effect.

For employers and policymakers, the findings put attention on what follows a job cut: access to training, time to reemployment, and whether new work pays enough to limit lasting losses. The evidence does not establish that AI alone caused the reported outcomes, but it suggests that counting eliminated roles may miss much of the disruption.

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Four Decades of Job Displacement

Goldman’s public research, published in a June 2026 “Top of Mind” report and a September summary, follows workers across more than 300 occupations using National Longitudinal Surveys that have tracked over 20,000 people through their careers. The researchers compared workers in occupations most exposed to technology in each decade with other workers. Their reported pattern is that technology-displaced workers took longer to regain employment, lost more than 3% in real pay upon reemployment, and saw weaker earnings growth over the next decade.

For the recent AI estimate, Goldman reportedly found no significant difference between its likely AI-displaced group and other laid-off workers for job losses before 2023, when AI adoption began to rise. That check may support the timing of its measure, but it does not establish that AI caused each later job loss. The classification combines job exposure, industry adoption, and position elimination rather than relying on workers’ accounts of why they were laid off.

The source material also reports that about 49% of long-tenured workers who returned to full-time work earned as much as before or more, down from about 62% two years earlier, citing the Bureau of Labor Statistics. That broader figure concerns long-tenured workers who found full-time work again; it is not specific to AI-related layoffs.

““comparable in magnitude””

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

How AI Displacement Is Measured

The reported figures are estimates rather than a direct count of people who say AI caused their job loss. The government survey does not ask that question, and Goldman’s method classifies workers using several indicators. A high score identifies people considered likely AI-displaced; it does not prove AI was the reason a particular employer eliminated a role.

The underlying October 29 client note is not public. Fortune reported its figures and quoted Mei, while the source material says other coverage repeated Fortune’s numbers. The full methods, calculations and limitations therefore cannot be independently reviewed here. Goldman also says it is too early to assess some potential differences, including by education and region. It remains unclear how many workers will find stable, comparable-paying work, or how the reported outcomes will change as AI adoption continues.

Tracking Reemployment and Pay

The next useful evidence will show whether the early pattern persists as more workers move through job searches and into new roles. That requires following reemployment time, wages and job stability, while distinguishing workers directly displaced by AI from those affected by other causes. Government surveys that ask about the reasons for job loss could help clarify that distinction; the current survey does not.

Goldman expects displacement costs to be greater during downturns, and its economists expect AI-related job losses to accelerate if the economy slows, according to the source material. That is an expectation, not a confirmed forecast of how many jobs will be affected. For now, the October estimate offers an early signal, while the longer-term effects on workers’ earnings and employment remain to be measured.

Key Questions

What did Goldman Sachs estimate about workers likely displaced by AI?

According to Fortune’s report on Goldman’s private note, workers likely displaced by AI since 2025 took 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.

Does the estimate prove AI caused those workers’ layoffs?

No. The government survey does not ask whether AI caused a job loss. Goldman used a score based on occupational exposure, industry adoption and whether a position was eliminated, so the group is described as likely AI-displaced, not confirmed as directly displaced by AI.

What does the historical research say about workers displaced by technology?

Goldman’s public research reports that technology-displaced workers took about a month longer to find work, lost more than 3% in real pay when reemployed, and had nearly 10 percentage points less real earnings growth over the following decade than workers who were not laid off.

What remains unknown about the recent AI figures?

The full client note is not public, and the estimate relies on an indirect classification rather than workers reporting that AI cost them their jobs. Longer-term outcomes, including differences by education and region, are not yet clear.

Source: ThorstenMeyerAI.com