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Goldman Sachs Study Highlights Long-Term Income Losses for AI-Displaced Workers and the Role of Retraining
When AI takes the wheel, who pays the price?
A new Goldman Sachs research note, released on September 11 2026, warns that the rapid rise of generative artificial intelligence (AI) could displace 6‑7 % of U.S. workers over the next decade. Drawing on four decades of individual‑level data, the study tracks 20,000 Americans and shows that those who lose jobs to automation face lasting income and employment challenges.
The research finds that displaced workers take an average of one month longer to secure new employment and earn about 3 % less than peers who remain in non‑automated roles. Workers who experience displacement early in their careers—between ages 25 and 35—accumulate wealth more slowly and are less likely to marry compared with workers who never experience displacement.
A key mechanism behind these outcomes is "occupational downgrading," the shift from higher‑skill, higher‑pay jobs to more repetitive, rule‑based roles. The same technological changes that eliminate a position often reduce the value of the skills workers bring to the market.
Age and education also shape the impact of displacement. Younger workers, especially those who are college‑educated and live in urban areas, are more exposed to AI‑driven job losses but tend to adjust more quickly, experiencing smaller earnings losses after displacement.
Retraining can mitigate some of the negative effects. The report shows that workers who complete at least four weeks of retraining within three years of losing a job are more likely to see higher wage growth and are less likely to return to unemployment over the following decade.
The Goldman Sachs note also references a LinkedIn post that reports the firm’s analysis found 16,000 U.S. jobs are being displaced each month in 2026. While the figure is not independently verified, it illustrates the scale of the issue the research seeks to quantify.
"Our analysis suggests that, similarly to previous waves of technological change, AI‑driven displacement could impose lasting costs on affected workers, worsening labor‑market outcomes for several years," the economists Pierfrancesco Mei, Jessica Rindels, and David Mericle wrote. They add that the effects could be substantially larger if displacement occurs during a recession.
The study’s findings have implications for policymakers, employers, and workforce development programs. If AI continues to automate routine tasks across industries, a sizable share of the workforce may need to transition to new roles. Retraining initiatives—especially those that begin soon after job loss—could help workers regain earnings momentum and reduce the likelihood of long‑term unemployment.
Goldman Sachs does not provide specific policy recommendations in the note, but the data suggest that investment in retraining and upskilling could be a cost‑effective strategy to soften the social and economic impact of AI displacement.
The research also underscores the importance of monitoring labor‑market trends. As AI technologies mature, the proportion of jobs that are vulnerable to automation may rise, potentially affecting income distribution, wealth accumulation, and demographic patterns such as marriage rates.
In summary, the Goldman Sachs study indicates that AI‑driven job displacement is likely to have lasting negative effects on earnings and employment stability, especially for workers displaced early in their careers. Younger, college‑educated workers fare better, and timely retraining can cushion the impact. Policymakers and employers should consider these dynamics when designing workforce development strategies.
A new Goldman Sachs research note, released on September 11 2026, warns that the rapid rise of generative artificial intelligence (AI) could displace 6‑7 % of U.S. workers over the next decade. Drawing on four decades of individual‑level data, the study tracks 20,000 Americans and shows that those who lose jobs to automation face lasting income and employment challenges.
The research finds that displaced workers take an average of one month longer to secure new employment and earn about 3 % less than peers who remain in non‑automated roles. Workers who experience displacement early in their careers—between ages 25 and 35—accumulate wealth more slowly and are less likely to marry compared with workers who never experience displacement.
A key mechanism behind these outcomes is "occupational downgrading," the shift from higher‑skill, higher‑pay jobs to more repetitive, rule‑based roles. The same technological changes that eliminate a position often reduce the value of the skills workers bring to the market.
Age and education also shape the impact of displacement. Younger workers, especially those who are college‑educated and live in urban areas, are more exposed to AI‑driven job losses but tend to adjust more quickly, experiencing smaller earnings losses after displacement.
Retraining can mitigate some of the negative effects. The report shows that workers who complete at least four weeks of retraining within three years of losing a job are more likely to see higher wage growth and are less likely to return to unemployment over the following decade.
The Goldman Sachs note also references a LinkedIn post that reports the firm’s analysis found 16,000 U.S. jobs are being displaced each month in 2026. While the figure is not independently verified, it illustrates the scale of the issue the research seeks to quantify.
"Our analysis suggests that, similarly to previous waves of technological change, AI‑driven displacement could impose lasting costs on affected workers, worsening labor‑market outcomes for several years," the economists Pierfrancesco Mei, Jessica Rindels, and David Mericle wrote. They add that the effects could be substantially larger if displacement occurs during a recession.
The study’s findings have implications for policymakers, employers, and workforce development programs. If AI continues to automate routine tasks across industries, a sizable share of the workforce may need to transition to new roles. Retraining initiatives—especially those that begin soon after job loss—could help workers regain earnings momentum and reduce the likelihood of long‑term unemployment.
Goldman Sachs does not provide specific policy recommendations in the note, but the data suggest that investment in retraining and upskilling could be a cost‑effective strategy to soften the social and economic impact of AI displacement.
The research also underscores the importance of monitoring labor‑market trends. As AI technologies mature, the proportion of jobs that are vulnerable to automation may rise, potentially affecting income distribution, wealth accumulation, and demographic patterns such as marriage rates.
In summary, the Goldman Sachs study indicates that AI‑driven job displacement is likely to have lasting negative effects on earnings and employment stability, especially for workers displaced early in their careers. Younger, college‑educated workers fare better, and timely retraining can cushion the impact. Policymakers and employers should consider these dynamics when designing workforce development strategies.
