Automation and the Workforce: A Firm-Level View from the 2019 Annual Business Survey

47 Pages Posted: 21 Nov 2022 Last revised: 25 Jan 2023

See all articles by Daron Acemoglu

Daron Acemoglu

Massachusetts Institute of Technology (MIT) - Department of Economics; Centre for Economic Policy Research (CEPR); National Bureau of Economic Research (NBER)

Gary Anderson

National Science Foundation

David Beede

U.S. Census Bureau

Catherine Buffington

US Census Bureau

Eric Childress

George Mason University

Emin Dinlersoz

Center for Economic Studies - US Census Bureau

Lucia Foster

U.S. Census Bureau - Center for Economic Studies

Nathan Goldschlag

Center for Economic Studies, U.S. Census Bureau

John Haltiwanger

University of Maryland - Department of Economics; National Bureau of Economic Research (NBER); Institute for the Study of Labor (IZA)

Zachary Kroff

U.S. Census Bureau

Pascual Restrepo

Boston University

Nikolas Jason Zolas

U.S. Census Bureau - Center for Economic Studies; University of California, Davis

Date Written: November 2022

Abstract

This paper describes the adoption of automation technologies by US firms across all economic sectors by leveraging a new module introduced in the 2019 Annual Business Survey, conducted by the US Census Bureau in partnership with the National Center for Science and Engineering Statistics (NCSES). The module collects data from over 300,000 firms on the use of five advanced technologies: AI, robotics, dedicated equipment, specialized software, and cloud computing. The adoption of these technologies remains low (especially for AI and robotics), varies substantially across industries, and concentrates on large and young firms. However, because larger firms are much more likely to adopt them, 12-64% of US workers and 22-72% of manufacturing workers are exposed to these technologies. Firms report a variety of motivations for adoption, including automating tasks previously performed by labor. Consistent with the use of these technologies for automation, adopters have higher labor productivity and lower labor shares. In particular, the use of these technologies is associated with a 11.4% higher labor productivity, which accounts for 20-30% of the difference in labor productivity between large firms and the median firm in an industry. Adopters report that these technologies raised skill requirements and led to greater demand for skilled labor but brought limited or ambiguous effects to their employment levels.

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Suggested Citation

Acemoglu, Daron and Anderson, Gary and Beede, David and Buffington, Catherine and Childress, Eric and Dinlersoz, Emin and Foster, Lucia and Goldschlag, Nathan and Haltiwanger, John C. and Kroff, Zachary and Restrepo, Pascual and Zolas, Nikolas Jason, Automation and the Workforce: A Firm-Level View from the 2019 Annual Business Survey (November 2022). NBER Working Paper No. w30659, Available at SSRN: https://ssrn.com/abstract=4282509 or http://dx.doi.org/10.2139/ssrn.4282509

Daron Acemoglu (Contact Author)

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Centre for Economic Policy Research (CEPR)

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Gary Anderson

National Science Foundation ( email )

David Beede

U.S. Census Bureau

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Catherine Buffington

US Census Bureau ( email )

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Eric Childress

George Mason University ( email )

Emin Dinlersoz

Center for Economic Studies - US Census Bureau ( email )

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Lucia Foster

U.S. Census Bureau - Center for Economic Studies ( email )

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Nathan Goldschlag

Center for Economic Studies, U.S. Census Bureau ( email )

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John C. Haltiwanger

University of Maryland - Department of Economics ( email )

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Institute for the Study of Labor (IZA) ( email )

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Zachary Kroff

U.S. Census Bureau

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Pascual Restrepo

Boston University ( email )

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Nikolas Jason Zolas

U.S. Census Bureau - Center for Economic Studies ( email )

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University of California, Davis ( email )

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