How Goldman Sachs Puts AI Layoffs In The Context Of Past Tech Shocks

🔍 Read the full analysis: How Goldman Sachs Puts AI Layoffs In The Context Of Past Tech Shocks on ThorstenMeyerAI.com

Buying for a business?Offer from Amazon

Get business pricing on monitors, keyboards and dev gear

• Business-only prices and quantity discounts
• Tax-exempt purchasing
• Multiple users, one account, clear invoices

Create a free Business account →Free to register

As an affiliate, we earn on qualifying purchases.Hide

Goldman Sachs estimates that workers likely displaced by AI since 2025 took about one month longer to find new jobs than other laid-off workers, according to a client note reported by Fortune. The analysis compares the early effects of AI-related job losses with earlier technology shocks, which Goldman’s published research associates with prolonged employment and earnings costs.

The note, dated October 29, was written by Goldman economist Pierfrancesco Mei and circulated to clients. Its contents are not publicly available. The figures have been reported by Fortune, which said the AI-exposed group was also about 10 percentage points more likely than other displaced workers to remain unemployed a year after losing a job. Those estimates should be treated as reported findings, not independently verified results.

Goldman’s approach is an estimate rather than a count of people who say AI eliminated their jobs: no government survey directly asks that question. According to the account of the note, the bank used Labor Department data on more than 15,000 people displaced between 2016 and 2025. It combined occupational AI exposure, the pace of AI adoption in each industry and whether a position was eliminated into a score. The top 30% were classified as “likely AI-displaced.” Goldman reportedly found no significant difference between that group and other laid-off workers for job losses before 2023.

Fortune also reported an age difference in the newer results. Workers aged 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. The account says AI-displaced workers were more likely to leave their former occupation or industry, but some who returned to work moved into jobs with similar or higher AI exposure, particularly among older workers.

Long Job Searches Can Leave Lasting Costs

The significance is not only whether a worker loses a job, but also how long the search lasts, what the next job pays and whether employment holds. A longer period out of work can affect household income and future earnings. Goldman’s earlier research suggests that, for past technology-related displacement, the costs did not end when workers found another position.

The findings also complicate the assumption that moving into a different job automatically protects someone from further technological change. The reported pattern of workers entering roles with similar or higher AI exposure points to a possible mismatch between displacement and retraining or job placement. The note does not establish why workers took those roles or whether AI later affected them.

For employers and policymakers, the analysis puts attention on support after layoffs: how quickly displaced workers find stable work, whether pay recovers and which groups face longer searches. Goldman’s historical research links retraining with better wage and unemployment outcomes, but it does not prove that a particular training program will produce the same results for workers displaced by AI today.

Products Worth Considering

Bose QuietComfort Headphones (2nd Gen), Wireless Noise-Cancelling Over-Ear Headphones, Black

AmazonView Latest Price

Samsung 27-Inch Odyssey QD-OLED G8 4K 240Hz Gaming Monitor

AmazonView Latest Price

Samsung Galaxy Tab S10 FE 128GB Wi-Fi Android Tablet, Blue

AmazonView Latest Price

As an affiliate, we earn on qualifying purchases.

Four Decades of Technology-Related Layoffs

The new estimate 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 examined more than 300 occupations and followed workers through National Longitudinal Surveys covering more than 20,000 people. It compared workers in technology-exposed jobs with workers whose jobs were in stable or growing occupations.

Goldman’s historical analysis found that workers displaced by technology took about one month longer to find work and earned more than 3% less in real pay when reemployed. 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 source material. Goldman also found that displaced 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 findings from historical data, not guarantees for current workers.

Government data on long-tenured displaced workers shows a related age gap, though it covers laid-off workers generally rather than those identified as AI-displaced. 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. The share of long-tenured workers who returned to full-time work earning as much as or more than before was about 49%, down from about 62% two years earlier, according to the Bureau of Labor Statistics figures cited in the source material.

““Comparable in magnitude””

— Pierfrancesco Mei, Goldman Sachs economist, as quoted in Fortune’s account of the client note

How Reliable Are the AI Estimates?

The October client note is not public, so the latest figures rely on Fortune’s reporting and cannot be checked against the original analysis here. The AI-displacement category is constructed from exposure, industry adoption and job-elimination measures; it is not a direct survey response confirming that AI caused an individual’s layoff.

The estimates also cover a period when AI adoption and labor-market conditions were changing. The reported differences do not, on their own, show that AI caused every job loss or that AI was the only reason for longer searches. Goldman’s method reportedly found no significant pre-2023 gap, but the post-2025 results remain early. Mei said outcomes by education and region were not yet assessable. The source material also says Goldman expects AI-related job losses to accelerate in an economic slowdown; that is an expectation, not a confirmed future outcome.

More Evidence as Displacement Develops

The next step is further evidence on whether the reported gap persists as more workers lose jobs and the effects can be tracked over time. Comparisons by age, education and region could clarify who faces the longest search and whether outcomes differ across local labor markets. Public access to the Goldman note or fuller methodological details would also allow readers to examine how its displacement score was built.

Government surveys can show employment and earnings outcomes for displaced workers, but the source material says they do not directly identify AI as the reason for a layoff. That leaves a measurement gap. For now, the Goldman note offers an early comparison with past technology shocks, while the scale and duration of AI’s effect on workers remain developing questions.

Key Questions

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

According to Fortune’s report on an unpublished Goldman client note, workers classified as likely AI-displaced since 2025 took about one month longer to find 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?

The reported method combined an occupation’s AI exposure, the rate of AI adoption in its industry and whether the position was eliminated. Goldman classified the top 30% of its score as likely AI-displaced; this is an estimate, not a direct report from workers that AI caused their layoff.

Are the reported results independently confirmed?

No. Goldman’s October client note is not public. The figures in this report come from Fortune’s account of the note and should be understood as reported estimates rather than independently checked results.

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

Goldman’s public research found that technology-displaced workers took longer to find new work, had lower real pay after reemployment and saw weaker real earnings growth over the following decade than workers who had not been laid off. Its findings also linked retraining within three years with better wage growth and a lower chance of unemployment again.

What remains unknown about AI-related layoffs?

The extent to which AI itself caused the layoffs, how results vary by education or region, and whether the reported job-search gap will persist are still unclear. The available government survey data does not directly ask workers whether AI cost them their jobs.

Source: ThorstenMeyerAI.com