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TL;DR
Goldman Sachs economist Pierfrancesco Mei compared workers likely displaced by AI since 2025 with other laid-off workers and found longer job searches and more unemployment a year later, according to Fortune’s report of a client note. Goldman’s public research on earlier technology shocks finds lasting pay and earnings effects, but the new AI estimates are not independently confirmed and the note is not public.
Goldman Sachs says workers likely displaced by AI since 2025 are taking longer to find new jobs and are more likely to remain unemployed a year after losing work than other laid-off workers, according to a client note reported by Fortune. The findings, by economist Pierfrancesco Mei, suggest the early effects may resemble past technology-related job losses, though Goldman said it is too early to assess the impact fully.
The note, dated October 29, is not public. The figures come from Fortune’s account the following day, which quotes the note; they have not been independently verified here. Fortune reports that workers Goldman classified as likely AI-displaced took about one month longer to find work than other displaced workers. They were also roughly 10 percentage points more likely to still be unemployed one year after losing their jobs.
Goldman’s estimate uses Labor Department data on laid-off workers, combined with measures of occupational exposure to AI, industry adoption and whether a position was eliminated. The analysis covered more than 15,000 workers who lost jobs between 2016 and 2025. Goldman classified the top 30% on its combined measure as “likely AI-displaced.” The source account says the analysis found no significant gap with other laid-off workers for job losses before 2023, when AI adoption began to rise.
The reported results show differences by age. Workers 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. Goldman also found that workers classified as AI-displaced were more likely to leave their previous occupation or industry. Some who returned to work, particularly older workers, took jobs with similar or higher exposure to AI, according to Fortune’s summary.
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 Longer Cost of Job Displacement
The findings focus attention on what happens after a layoff, not just the number of jobs cut. A longer search can mean an extended period without wages, while a return to work does not necessarily restore a worker’s previous pay or career path. That distinction matters to workers, employers and policymakers weighing the labor-market effects of AI.
Goldman’s public research on earlier technology-related displacement offers a longer-term comparison. It found displaced workers took about a month longer to find new jobs, lost more than 3% in real pay when reemployed, and experienced nearly 10 percentage points less real earnings growth over the following decade than workers who had not been laid off. Those historical results do not prove that AI will produce the same outcomes, but they show why early reemployment figures alone may not capture the full cost.
The reported note also points to a potential role for retraining. In Goldman’s historical data, technology-displaced workers who retrained within three years had about two percentage points more real wage growth over a decade and a roughly 10-point lower chance of becoming unemployed again. These are associations in the historical analysis, not a guarantee that training will produce the same results for current workers.
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How Goldman Built Its Comparison
There is no government survey that asks workers directly whether AI caused them to lose a job. Goldman therefore used a proxy based on existing Labor Department data, scoring occupations and industries for AI exposure and adoption and considering whether the job itself had been eliminated. That approach can identify a group with higher potential exposure, but it cannot establish that AI caused each individual layoff.
The comparison draws on Goldman’s public research, including a June 2026 “Top of Mind” report and a September summary by Mei and colleagues Jessica Rindels and David Mericle. That work followed workers across more than 300 occupations using National Longitudinal Surveys covering over 20,000 people. It examined workers exposed to earlier waves of technology across several decades and found slower reemployment and weaker subsequent earnings than for workers in stable or growing occupations.
Government data cited in the source material also show age-related differences among long-tenured displaced workers, though those figures cover layoffs generally, not AI-related job losses. By January 2026, 72.9% of workers aged 25 to 54 in that group were working again, compared with 57.3% of workers aged 55 to 64. The data provide labor-market context but do not establish that AI drove the gap.
““comparable in magnitude””
— Pierfrancesco Mei, Goldman Sachs economist, as quoted in Fortune’s account of the client note
Limits of the Early AI Estimates
The October client note is not publicly available, and the AI-related figures are reported through Fortune rather than independently checked against the underlying analysis. Goldman’s classification is an estimate: because the government survey does not ask whether AI caused a layoff, the method cannot distinguish AI-driven job losses from layoffs caused by other factors in every case.
The reported results cover a relatively early period of AI adoption and do not settle the longer-term effects on pay, job quality or career progression. Mei also said it was too early to assess differences by education and region. The source material says Goldman expects AI-related losses to accelerate if the economy slows and that displacement costs are larger in downturns; the scale and timing of any such effect remain uncertain.
More Data Will Test the Pattern
The next test will be whether subsequent labor-market data show the same gap in reemployment and unemployment duration as AI adoption spreads. A longer follow-up will be needed to track wages, job stability and occupation changes, rather than only the first return to work. Goldman’s public research provides historical comparisons, while the newer estimates will need further data to show whether the pattern persists.
For now, the note presents an early warning rather than a final accounting of AI’s employment effects. Further results by age, education and region could clarify which workers face the longest searches and whether retraining is associated with stronger outcomes for this newer group. No specific publication date for additional findings is given in the source material.
Key Questions
What did Goldman Sachs find about likely AI-displaced workers?
According to Fortune’s report of a Goldman client note, workers classified as likely AI-displaced since 2025 took about one month longer to find new work and were roughly 10 percentage points more likely to remain unemployed a year after losing a job than other laid-off workers.
How did Goldman identify workers likely displaced by AI?
Goldman combined measures of occupational AI exposure, industry adoption and whether a position was eliminated, using Labor Department data on displaced workers. The method is a proxy, not direct proof that AI caused an individual layoff.
Are the new figures independently confirmed?
The client note is not public. The figures are drawn from Fortune’s report quoting the note and have not been independently verified here.
What does Goldman’s historical research say about technology layoffs?
Goldman’s public research found that workers displaced by earlier technological change took longer to find jobs and had weaker pay and earnings growth than comparison groups. Those historical findings do not establish that AI will have identical effects.
What remains unknown about AI’s effect on jobs?
The long-term effects on wages, job stability and career paths are not yet clear. Goldman also said it is too early to assess differences by education and region, and its proxy cannot determine the cause of every layoff.
Source: ThorstenMeyerAI.com
