The Productivity Puzzle: AI, Technology Adoption and the Workforce

Erin Henry, Pierre Daniel Sarte and Jack Taylor
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Jack Taylor: https://www.richmondfed.org/research/people/taylor

Richmond Fed Economic Brief, 2024, vol. 24, issue 25

Abstract: In 1987, economist Robert Solow said, "You can see the computer age everywhere but in the productivity statistics."1 This quote underscores the challenges in tracing the effects of information technology and automation on productivity and the economy at large. Understanding the role of technology in labor productivity growth remains an ongoing quest in economics, one made even more pertinent by recent advances in artificial intelligence (AI) as well as the further adoption of generative AI and large language models (LLMs). Estimates of the effect of AI on economic and productivity growth range from reasonably bullish to more sedate:2 Goldman Sachs predicted that AI would lead to a $7 trillion increase in global GDP and a 1.5 percent per year increase in U.S. productivity growth over the next decade.3 The McKinsey Global Institute forecasts that generative AI could lead to a 1.5-3.4 percentage point increase in average annual GDP growth across the developed world in the next decade.4 Economist Daron Acemoglu estimated more muted effects from AI over the next decade: increases of 0.07 percent in productivity annually and 0.9 percent to 1.8 percent in GDP.5 Our article suggests that the observation embodied in Solow's quote is still pertinent today, even in the current age of AI and automation. A direct and concrete relationship between technological deepening and productivity remains elusive at best. It also suggests estimates more in line with Acemoglu's work and points to an alternative mechanism as a driver of productivity growth: the age composition of the U.S. workforce.

Keywords: technology; AI; productivity (search for similar items in EconPapers)
Date: 2024
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