Two curious things are happening to the economy in 2026. On one hand, economic expansion is still going strong despite job growth slowing to a trickle, suggesting productivity among those currently employed is rising. But by many measures, productivity growth has barely budged in recent years, and slowed in the first quarter of 2026. Those things usually can’t be true at the same time.
Technologists claim AI will help optimize workflows and supercharge the U.S. economy’s productivity—a measure of how efficiently resources such as labor are being converted to goods and services. While that growth has yet to show up in the data, AI might be responsible for the discrepancy in productivity statistics so far.
In certain professions, employees who use AI are more likely to produce the same amount of work in less time, potentially saving an entire workday a week, according to a study by the London School of Economics last year. Economists call this an example of capital deepening, or when workers gain access to better tools and their individual productivity rises as a result—like when a construction worker trades in a shovel for a mechanical excavator.
There’s another example of this process that might be more analogous to the age of AI, put forward in a research brief published Tuesday by the Federal Reserve Bank of San Francisco. Just as with companies spending lavishly on AI integration today, economists analyzing the first days of the Internet in the early and mid-1990s might have been similarly puzzled. Employees suddenly had access to groundbreaking technology, but many firms remained stuck in the trenches of a “productivity paradox” that plagued the U.S. between the 1970s and 1990s as massive investments in IT failed to translate to improved efficiency.
