What 40 Years Of Technology Shocks Reveal About AI-Driven Job Cuts

🔍 Read the full analysis: What 40 Years Of Technology Shocks Reveal About AI-Driven Job Cuts on ThorstenMeyerAI.com

Workers likely displaced by AI since 2025 have taken longer to find new jobs and have been more likely to remain unemployed a year after losing work than other laid-off workers, according to a Goldman Sachs client note reported by Fortune. The findings echo four decades of Goldman research on technology-related job losses, which found that the effects could persist in workers’ pay and earnings long after they were rehired.

Goldman economist Pierfrancesco Mei compared workers whose job losses were classified as likely related to AI with other displaced workers. Fortune reported that the AI-exposed group took about one month longer to find new work and was roughly 10 percentage points more likely to still be unemployed a year after losing a job. The note is for Goldman clients and is not publicly available; these figures come from Fortune’s account and are not independently confirmed here.

Goldman’s estimate draws on Labor Department survey data for more than 15,000 people who lost jobs between 2016 and 2025. The researchers combined the AI exposure of a worker’s occupation, the pace of AI adoption in the industry, and whether the job itself was eliminated. They classified the highest-scoring 30% as “likely AI-displaced.” Goldman reportedly found no significant difference between this group and other laid-off workers for job losses before 2023, when AI adoption began to rise.

The reported age differences were substantial: workers aged 35 and older took about five weeks longer than comparable laid-off workers to return to full-time work, compared with about three weeks for those under 35. Goldman also found that AI-displaced workers were more likely to leave their occupation or industry. Yet some rehired workers, particularly older ones, ended up in jobs with similar or higher exposure to AI, according to Fortune’s account.

The Costs Continue After Rehiring

The findings shift attention from the number of announced cuts to what happens to workers afterward: how long job searches last, what new roles pay, and whether those jobs endure. A layoff count cannot capture those effects. If workers face longer periods without work or accept lower-paying roles, the economic impact can continue well beyond the date a company announces a reduction.

Goldman’s public research on earlier technology-related displacement offers a warning, not a forecast for every AI-affected worker. It found that workers who lost jobs to technology took about a month longer to find work and experienced a real pay drop of more than 3% when rehired. Their real earnings growth over the following decade was nearly 10 percentage points lower than for workers who had not been laid off, according to the research described in the source material.

Those patterns matter to employers and policymakers as well as workers. Companies may reduce roles while introducing AI, but the reported evidence suggests that the costs of displacement can outlast the initial restructuring. The effects may also be uneven: older workers took longer to return to full-time employment in Goldman’s new estimate, and government data cited in the source shows a wider reemployment gap for older long-tenured workers overall.

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Four Decades of Displacement Data

Goldman’s historical comparison comes from 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 over several decades and tracked workers through National Longitudinal Surveys that have followed more than 20,000 people over their careers.

That research found technology-displaced workers had slower reemployment and weaker pay outcomes than workers laid off from stable or growing occupations. It also reported that workers who retrained within three years had about two percentage points more real wage growth over the next decade and a roughly 10-point lower chance of becoming unemployed again. Those results describe historical associations; they do not establish that retraining will produce the same outcome for every worker affected by AI.

Government figures cited in the source provide another point of comparison, but cover all long-tenured laid-off workers, not only those displaced by AI. By January 2026, 72.9% of workers aged 25 to 54 in that group were working again, compared with 57.3% of those aged 55 to 64. 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 in the source material.

„“Comparable in magnitude”“

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

Limits of the Early AI Estimate

The new figures rely on an estimate rather than a government survey that directly asks whether AI caused someone to lose a job. Goldman’s classification combines occupation-level AI exposure, industry adoption and job elimination, so it identifies workers considered likely to have been displaced by AI; it does not prove AI caused each individual layoff.

The underlying client note is not public. The new numbers are reported by Fortune and should be treated as reported findings, not independently verified results. The source also says it is too early to assess differences by education and region. It remains unclear whether longer job searches and the other reported outcomes will continue as AI adoption changes or how much they reflect other economic conditions.

Goldman’s historical research found displacement costs were larger in downturns. Its economists expect AI-related job losses to speed up if the economy slows, but that is an expectation, not a confirmed outcome. The source does not provide a specific forecast for the scale or timing of future cuts.

Tracking Reemployment and Pay

The next evidence will come from following displaced workers over time: whether they return to full-time work, how long their searches last, what they earn afterward, and whether they remain in their new roles. Further data could also clarify how outcomes differ by age, education, region and industry, dimensions Goldman said were not yet assessable in the early results.

Readers should distinguish the reported AI estimates from the longer historical record as new research emerges. The Goldman note’s method depends on how researchers identify probable AI displacement, while government labor data measures broader groups of laid-off workers. For now, the central finding is a reported early pattern—not a final accounting of AI’s effect on employment or a prediction that every displaced worker will face the same costs.

Key Questions

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

Fortune reported that workers classified as likely displaced by AI since 2025 took about one 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.

How did Goldman identify likely AI-related job losses?

Goldman reportedly combined a job’s AI exposure, the pace of AI adoption in its industry and whether the position was eliminated. Workers in the highest-scoring 30% were classified as “likely AI-displaced.”

Are the new figures independently confirmed?

No. The Goldman note was sent to clients and is not public. The figures in the source material come from Fortune’s report, so they should be understood as reported estimates rather than independently verified results.

What does the historical research say about technology-related layoffs?

Goldman’s public research found that technology-displaced workers took longer to find jobs, lost more than 3% in real pay when rehired and had nearly 10 percentage points less real earnings growth over the following decade than workers who were never laid off.

Does the report show that retraining guarantees a better outcome?

No. Goldman’s historical data linked retraining within three years to somewhat stronger real wage growth and a lower chance of later unemployment. That association does not guarantee the same results for every worker or for people displaced by AI.

Source: ThorstenMeyerAI.com