The Rapid Adoption of Generative AI
The National Bureau of Economic Research (NBER) is a leading nonprofit research organization in the U.S. that focuses on understanding economic trends, cycles, and issues through rigorous research. Founded in 1920 and based in Cambridge, Massachusetts, NBER provides insights into critical economic topics, ranging from employment and productivity to health and innovation. Known for developing economic data and tools used by policymakers, academics, and analysts, NBER’s work is widely cited in economics and has a significant influence on economic policy and theory.
In September 2024, NBER published "The Rapid Adoption of Generative AI" by Alexander Bick, Adam Blandin, and David J. Deming examining the swift uptake of generative AI among U.S. adults. It highlights that over 24% of workers used generative AI recently, marking faster adoption than past technologies like personal computers. The study emphasizes generative AI’s role as a general-purpose technology, finding applications across diverse tasks in professional and domestic settings.
The following summary captures the core findings and trends discussed in the paper.
Widespread Adoption: Generative AI saw rapid adoption, with 39% of the U.S. adult population (18-64) using it, and nearly 11% of employees using it daily.
Comparative Speed: Generative AI adoption outpaced both the PC and the Internet, with faster uptake especially at home due to portability and lower costs.
Diverse Usage Across Occupations: Generative AI is utilized across various sectors, including management, business, and even blue-collar jobs, highlighting its general-purpose nature.
Task Application: It assists with a broad range of tasks, including writing, administrative tasks, and data interpretation, which reflects its versatility and relevance for diverse workflows.
Usage Patterns: Adoption is more common among younger, more educated, and higher-income demographics, suggesting parallels to technology adoption patterns seen in previous technology waves.
Gender Differences: Men are slightly more likely than women to use generative AI at work, diverging from past technology adoptions like PCs, where women led due to administrative roles.
Intensive Daily Use: Nearly 25% of users spend over an hour daily on generative AI for work tasks, especially in jobs that require data interpretation, writing, and coding.
Productivity Impacts: Studies indicate a 25% productivity increase when using generative AI in task-specific scenarios, though the actual impact on overall productivity remains speculative.
Work Hour Assistance: Generative AI currently assists in 0.5-3.5% of U.S. work hours, with potential to increase labor productivity by 0.125-0.875 percentage points at current usage levels.
Future Tracking and Trends: The survey intends to continue monitoring AI adoption and explore its evolving economic impact, considering shifts in usage patterns and technology advances.
For more details, see the full paper here.
These findings underscore the transformative potential of generative AI, not just in specialized fields but across diverse job sectors. As the technology embeds itself deeper into both professional and personal workflows, its accelerated adoption highlights a shift in how technology can redefine productivity and accessibility in everyday tasks.
Looking ahead, tracking this technology’s influence on productivity and broader economic impacts will be crucial, as it continues reshaping how we approach work and harness technology for various aspects of life.
Thanks for this clear summary of the NBER work. I hadn't seen their study and it provides confirmation of trends we're all absorbing.