AI Videos

Nicholas Bloom | The Impact of AI on Productivity

Nick Bloom, Stanford economist, presented a data‑driven assessment of artificial intelligence’s effect on productivity at a San Francisco Fed event. He emphasized that the analysis relies on a large‑scale survey of roughly 6,000 CFOs and CEOs across four countries, rather than theoretical speculation, to gauge how firms are actually deploying AI tools. Bloom highlighted the stark contrast between historical trends—U.S. labor productivity has been falling from about 3‑4% in the 1950s to near‑zero growth today—and the wildly divergent forecasts for AI, ranging from a modest 0.1% boost to a transformative 10‑20% annual increase. The survey revealed that while individual usage sits at 30‑40%, firm‑level adoption appears low in official census data (around 17%) but much higher in payment‑processor metrics (approaching 50%). He noted that political affiliation influences AI usage, with Democrats more likely to adopt the technology, and cited anecdotal evidence such as RAMP’s transaction‑based AI adoption figures. Bloom also described the rigorous two‑step recruitment process—phone verification followed by monthly email panels—that yields a roughly 30% response rate from senior executives, ensuring the data’s credibility. The findings carry significant policy implications: central banks need reliable measures of AI‑driven productivity to calibrate inflation forecasts and interest‑rate decisions. Bloom’s 50/50 assessment—AI could either revive growth or continue the long‑term slowdown—underscores the urgency for better firm‑level data and ongoing monitoring as the technology matures.