Fed's Williams Argues U.S. Dynamism, Not Just AI, Drives Productivity Gains

Fed's John Williams suggests recent productivity gains stem not only from AI but also from the U.S. economy's underlying dynamism, such as new business formation and operational improvements.

This view is supported by data showing productivity was already improving before the AI boom and by recent Fed research highlighting AI's uncertain and concentrated impact.

Therefore, the Fed is expected to maintain a balanced policy stance, observing real data on productivity and labor costs rather than reacting prematurely to AI hype or dismissing the gains.

New York Fed President John Williams has offered a nuanced view that the recent pickup in U.S. productivity isn't solely driven by the AI boom.

He argues that a significant part of this improvement comes from the U.S. economy's fundamental dynamism—things like the formation of new companies, better resource allocation, and operational upgrades that were happening even before AI became a major headline.

This perspective is grounded in solid evidence. First, government data shows that U.S. productivity was already on an upward trend throughout 2024 and 2025, well before the widespread corporate investment in AI began in 2026. For instance, productivity rose a solid 2.3% in 2024, indicating a pre-existing positive momentum.

Second, recent research from the Federal Reserve system itself supports this cautious interpretation. Both the New York and San Francisco Feds have published papers noting that AI's adoption is currently concentrated among a few large firms, and its broader macroeconomic impact remains uncertain. This reinforces Williams' point that we can't attribute all recent gains to AI just yet.

So, what does this mean for Fed policy? It suggests a "wait-and-see" approach is the most sensible path. The Fed shouldn't rush to tighten policy based on fears of an "AI hype bubble" overheating the economy. At the same time, it shouldn't dismiss these productivity gains as temporary or insignificant.

Instead, the central bank will likely focus on the hard data, especially the relationship between productivity and wages, which determines unit labor costs (ULC). If productivity growth outpaces wage growth, it's disinflationary, giving the Fed more room to be patient or even consider rate cuts. This balanced view is key to navigating the economic opportunities and risks presented by AI.

Unit Labor Costs (ULC): The average cost of labor per unit of output. It's calculated as the ratio of total labor compensation to real output. A falling ULC is generally considered disinflationary.
Dynamism: In economics, this refers to the rate at which an economy changes, including the birth and death of firms, job creation and destruction, and the reallocation of resources.

Fed's Williams Argues U.S. Dynamism, Not Just AI, Drives Productivity Gains

Fed's John Williams suggests recent productivity gains stem not only from AI but also from the U.S. economy's underlying dynamism, such as new business formation and operational improvements.

This view is supported by data showing productivity was already improving before the AI boom and by recent Fed research highlighting AI's uncertain and concentrated impact.

Therefore, the Fed is expected to maintain a balanced policy stance, observing real data on productivity and labor costs rather than reacting prematurely to AI hype or dismissing the gains.

New York Fed President John Williams has offered a nuanced view that the recent pickup in U.S. productivity isn't solely driven by the AI boom.

Unit Labor Costs (ULC): The average cost of labor per unit of output. It's calculated as the ratio of total labor compensation to real output. A falling ULC is generally considered disinflationary.
Dynamism: In economics, this refers to the rate at which an economy changes, including the birth and death of firms, job creation and destruction, and the reallocation of resources.