AI Spending Is Lifting Growth Before Productivity Gains Reach Most Workers

Artificial intelligence is contributing to U.S. economic growth, but the clearest gains so far are coming from business investment and a stock-market rally—not a broad rise in worker productivity. Economists say AI’s effects on jobs and output remain limited or concentrated in particular sectors, even as companies begin adopting the technology more widely.

Productivity measures how much workers produce in a given amount of time. AI could raise it by helping employees complete tasks faster, or by automating work and allowing remaining employees to produce more. So far, evidence of either effect across the wider economy is mixed.

Goldman Sachs (https://www.goldmansachs.com) economists have found stronger productivity growth over the past five years in technology and related fields, including scientific research, than in the period before the pandemic. They say AI may have contributed. JPMorgan Chase (https://www.jpmorganchase.com) economists, by contrast, found no strong relationship between AI use and productivity across industries in earlier research. In more recent work, they found no apparent link between AI use and slower employment growth outside the technology sector.

Labor-market data also show little change in the overall mix of jobs most exposed to AI. The Yale Budget Lab (https://budgetlab.yale.edu/) found that occupations highly exposed to ChatGPT (https://chatgpt.com) accounted for about 18.2% of U.S. workers in the three months ended November 2022, shortly after its release. By the three months ended in August 2026, the share was about 18.3%.

That stability does not rule out disruption in specific groups. The Budget Lab found that the occupational mix among recent college graduates is changing faster than it is for older workers. A Stanford (https://www.stanford.edu) study similarly found worsening job prospects for young people in fields where generative AI can readily automate tasks, including software development. But workers under 30 make up only about a quarter of the roughly two million U.S. software developers, a small share of total employment.

The economic impact of AI investment is easier to see. Business spending on software and information-processing equipment accounted for two-thirds of U.S. GDP growth in the first half of 2026. That spending supports demand for technology even as companies work out how to turn tools into lasting efficiency improvements.

Adoption is rising, but remains far from universal. In a recent Census Bureau (https://www.census.gov) survey, about 10% of businesses reported using AI, compared with roughly 6% a year earlier and 5% when ChatGPT was released. Economists say the benefits may take time to emerge as businesses redesign processes and employees learn where the tools are useful.

University of Toronto (https://www.utoronto.ca) economist Joshua Gans (https://www.rotman.utoronto.ca/the-rotman-experience/our-community/people/gans-joshua/) has compared the adjustment to the early use of desktop computers, when workers needed time to learn how the technology could change their work. Many AI users still try isolated tasks, encounter frustrating results and conclude the tool is not worth the effort, he said. The larger productivity gains, Gans argues, depend on figuring out how to transform work rather than simply adding AI to existing routines.

For business leaders, the current evidence points to a gap between investment and realized productivity. The next test is whether broader adoption leads companies to change workflows—and whether those changes produce measurable gains beyond technology-heavy industries.

Cited: https://www.wsj.com/tech/ai/ai-worker-productivity-economy-77498195?st=tNL7qB

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