Research from Goldman Sachs, released on Monday, indicates that industries increasingly embracing artificial intelligence are witnessing slower employment growth and higher unemployment rates.
The Chief Economist at Goldman Sachs, Jan Hatzius, pointed to significant correlations between AI adoption and declining labor market conditions within U.S. nonmanufacturing industries in a report titled “Global Views: Downside Growth Risks.” This suggests that while the AI boom may bring economic advantages, it might also lead to disruptions in American jobs. However, it’s worth noting that these correlations don’t definitively prove that AI is directly responsible for the job losses.
Hatzius mentioned in the report that signs of AI’s impact are now evident beyond the tech sector.
The analysis revealed that sectors with a higher proportion of businesses utilizing AI tended to have slower employment growth and increased unemployment when compared to those with lower adoption rates.
Goldman’s statistical model indicated that a 10% rise in industry-level AI adoption aligned with around a 0.9% drop in employment growth. Similarly, a corresponding analysis pointed to a 0.9% increase in unemployment relative to average rates from 2015 to 2019.
The report, utilizing data from the U.S. Census Bureau, Bureau of Labor Statistics, and Integrated Public Use Microdata Series, confirmed the statistical significance of these relationships.
The findings span various industries, including financial services, insurance, and telecommunications, raising concerns about how automation might alter employment in sectors previously thought to be less vulnerable to technology-driven job losses.
Goldman’s newer insights suggest a broader trend than what they described in September, which indicated that the hiring challenges related to AI were concentrated in a limited range of industries and job roles.
The earlier report had suggested that entry-level positions might be particularly affected as companies increasingly deploy AI to carry out tasks traditionally allocated to junior employees.
Evidence of AI’s integration into typical business operations is also visible in federal data. The Census Bureau indicated in May that around 20% of American businesses were employing AI, with adoption rates nearing 40% in the information sector and approximately 34% in finance and insurance.
Earlier in 2026, Goldman Sachs estimated that AI had decreased monthly U.S. job growth by about 16,000 positions over the last year, contributing to a roughly 0.1 percentage point rise in the unemployment rate.
There’s still a belief at Goldman that AI could create new job opportunities in areas where technology enhances rather than replaces human roles.
Hatzius also cautioned that the broader economic uplift from significant investments in AI is nearing its maximum potential.
He anticipates that the growth benefits from AI investments will peak around late 2026 or early 2027, as spending on the technology continues to rise but at a decelerating rate compared to the overall economy. The report estimated that increases in AI-related stocks had bolstered U.S. consumer spending growth by approximately 0.4% over the past year, an effect which Goldman believes will lessen over time.
Despite the emerging worries regarding employment, Goldman Sachs remains optimistic that AI investment will ultimately lead to higher productivity and corporate profits across the economy.
However, the report warns that the labor market disruptions accompanying these gains could have negative short-term economic repercussions, creating an escalating challenge for American workers as businesses quicken their technology adoption.
