🔍 Read the full analysis: Could The Aftermath Of AI Layoffs Resemble Past Tech Disruptions? on ThorstenMeyerAI.com
Get smart everyday buys delivered free with Prime
- Fast, free delivery on millions of items
- Prime Video, Amazon Music and more included
- Member-only deals all year
TL;DR
A Goldman Sachs note, reported by Fortune, estimates that workers likely displaced by AI since 2025 took 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. The note is not public, and Goldman’s method estimates AI displacement rather than confirming the cause of each job loss. Its historical research suggests technology-related layoffs can also bring lasting pay and employment costs.
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 remain unemployed a year after losing their jobs. The findings suggest the aftermath may resemble earlier technology-driven job losses, but the underlying client note is not public and the figures are reported rather than independently verified.
Goldman economist Pierfrancesco Mei prepared the note dated October 29. Fortune reported its findings the next day, quoting the client research. Goldman’s estimate is not based on a government survey asking whether AI caused a person’s job loss; no such survey is available. Instead, the bank constructed a measure of likely AI displacement using occupational exposure to AI, industry adoption, and whether a position was eliminated.
According to Fortune’s account, Goldman examined more than 15,000 people who lost jobs between 2016 and 2025, using Labor Department displaced-worker data. It classified the top 30% on its combined measure as “likely AI-displaced.” The bank found no significant difference between this group and other displaced workers for job losses before 2023, Fortune reported. For losses since 2025, it estimated longer job searches and a greater chance of still being unemployed one year later.
The reported note also identifies an age difference: 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. Goldman also found that AI-displaced workers were more likely to leave their former occupation or industry. Some who found new jobs, particularly older workers, returned to roles with similar or higher AI exposure, according to Fortune.
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.
Powered by Thorsten Meyer AI
The Costs Can Outlast the Layoff
The job-loss count captures only the start of the disruption. A longer search can mean lost wages, savings pressure and a difficult return to stable employment; a lower-paying job can affect earnings for years. Goldman’s public historical research, separate from the unpublished note’s recent estimates, found workers displaced by technology took about one month longer to find work and lost more than 3% in real pay when reemployed, compared with workers laid off from stable or growing occupations.
That research also found a longer-term earnings penalty: over the following decade, the real earnings growth of technology-displaced workers was nearly 10 percentage points lower than that of people who had not been laid off, according to Goldman’s published work. The figures describe historical patterns, not a forecast for every worker displaced by AI. Still, they show why evaluating AI’s labor impact requires looking beyond the number of announced cuts to reemployment, pay and job stability.
The findings are relevant to workers, employers and policymakers because AI adoption may change both which jobs are eliminated and what work remains available. If displaced workers move into jobs with similar AI exposure, they may face further changes as technology spreads. Goldman’s note, as reported, also says displacement costs are larger during economic downturns, raising concern that a slowdown could make reemployment harder.
Popular right now
De'Longhi Rivelia Automatic Espresso Machine with Milk Frother
Dyson Car+Boat Cordless Handheld Vacuum
De'Longhi Magnifica Evo Fully Automatic Espresso Machine with Manual Milk Frother, Silver
As an affiliate, we earn on qualifying purchases.
How Goldman Built Its Comparison
Goldman’s longer historical comparison draws on public research published in its June 2026 “Top of Mind” report and a September summary. Mei and colleagues Jessica Rindels and David Mericle tracked workers across more than 300 occupations and several decades, using National Longitudinal Surveys that have followed more than 20,000 people through their careers. They compared workers in occupations more exposed to technological change with workers in other jobs.
The earlier findings point to more than a temporary delay in finding work. Goldman reported that workers displaced by technology experienced weaker real earnings growth over time. Its historical analysis also found better outcomes among people who retrained within three years: about 2 percentage points more real wage growth over a decade and a roughly 10-point lower chance of becoming unemployed again than among those who did not retrain. These are associations in Goldman’s historical data, not proof that retraining alone caused the difference.
Government data offer a separate view of the challenges facing laid-off workers, though it does not identify AI as the cause. The Bureau of Labor Statistics reported that 72.9% of long-tenured workers aged 25 to 54 were working again by January 2026, compared with 57.3% of workers aged 55 to 64. Among long-tenured workers who returned to full-time jobs, about 49% earned as much as before or more, down from about 62% two years earlier, according to the source material’s account of BLS data.
““comparable in magnitude””
— Pierfrancesco Mei, Goldman Sachs economist, as quoted in Fortune
AI Attribution Remains an Estimate
The central limitation is that Goldman’s recent figures rely on an estimated category of likely AI displacement, not direct confirmation that AI caused each job loss. The bank combined measures of exposure, industry adoption and position elimination; those factors may identify workers affected by AI, but they do not establish the reason for every employer’s decision. The client note itself is not publicly available, so the reported findings cannot be checked against the full analysis.
It is also too soon to know whether the pattern will persist, how it varies across regions and education levels, or how many workers will find jobs with better pay and stability. The reported data cover an early period of AI adoption and do not establish that AI alone caused the observed differences. Goldman’s warning about larger costs in a downturn is a research finding about displacement more generally; the timing and scale of any future AI-related layoffs remain uncertain.
More Data Will Test the Pattern
The next test will be whether later labor-market data show the same gaps in job-search duration, unemployment and earnings as AI adoption spreads. Goldman’s published historical work provides a comparison, but clearer conclusions about the recent wave will require longer follow-up and better evidence about why individual jobs ended. The Labor Department’s displaced-worker data can track outcomes, but it does not directly label a layoff as AI-caused.
Goldman has pointed to education and region as areas where the impact is still too early to assess, according to Fortune’s report. Policymakers and employers will also be watching whether retraining is followed by durable employment and wage gains, rather than treating training participation by itself as proof of success. For workers, the immediate measure remains whether they can return to full-time work and maintain or improve their previous earnings.
Key Questions
What did Goldman Sachs report about workers likely displaced by AI?
According to Fortune’s account 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 later than other laid-off workers.
Did Goldman confirm that AI caused those job losses?
No. Goldman built an estimate based on occupational AI exposure, industry adoption and whether a position was eliminated. The method identifies workers considered likely to have been displaced by AI; it does not confirm the cause of each layoff.
Why are older workers a particular concern?
The note, as reported by Fortune, estimated that workers aged 35 and older took about five weeks longer than comparable laid-off workers to return to full-time work, versus about three weeks for those under 35. Separate government data also show lower reemployment rates for older long-tenured workers, though those figures do not isolate AI-related layoffs.
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. These are reported associations, not a guarantee that retraining will produce the same outcomes for every worker.
Source: ThorstenMeyerAI.com
