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Goldman Sachs forecasts 9% of workers could face AI displacement

October 22, 2026 8:52 AM EDT

Investing.com -- Goldman Sachs released research Thursday examining how artificial intelligence may affect employment, drawing on historical data about technology-driven labor displacement.

The investment bank analyzed three different methods to measure how technology has historically displaced workers. The research aims to quantify potential AI-related job disruption as companies weigh whether labor cost savings will justify their AI investments.

Goldman Sachs found that each 1% increase in labor productivity from technological innovation has historically caused a temporary 0.3 to 0.4 percentage point rise in unemployment, which typically fades after two years. This increase stems from a 0.5% to 0.6% cumulative rise in job losses and a smaller 0.2% reduction in hiring.

The bank's industry-level analysis showed similar effects on unemployment and job changes, though it found larger impacts on job losses during the late 1990s and following bigger productivity gains.

A third approach examined 25 occupations that faced major technological disruption, including photo processors, proofreaders, and file clerks. These occupations saw average job losses of 25% after five years when technology made their work redundant. Job separations increased more than hiring decreased in these cases.

Goldman Sachs projects that a 15% productivity increase from AI could temporarily displace around 9% of workers during the transition period. The bank noted that employment reductions typically result more from job losses than slower hiring, suggesting that tracking AI-related layoffs could serve as a real-time indicator.

The research indicates that automation-related labor disruption remains limited when the overall economy is healthy but accelerates during economic slowdowns. Goldman Sachs expects the AI labor market transition will be manageable if economic activity remains healthy, but warns that AI-related labor disruptions could amplify broader business cycles.



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