A.I. Adoption in America: Who, What, and Where

Journal of Economics and Management Strategy, Forthcoming

66 Pages Posted: 10 Jan 2024

See all articles by Kristina McElheran

Kristina McElheran

University of Toronto - Strategic Management

J. Frank Li

Stanford University

Erik Brynjolfsson

National Bureau of Economic Research (NBER); Stanford

Zachary Kroff

U.S. Census Bureau

Emin Dinlersoz

Center for Economic Studies - US Census Bureau

Lucia Foster

U.S. Census Bureau - Center for Economic Studies

Nikolas Jason Zolas

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

Date Written: December 22, 2023

Abstract

We study the early adoption and diffusion of five AI-related technologies (automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition) as documented in the 2018 Annual Business Survey of 850,000 firms across the United States. We find that fewer than 6\% of firms used any of the AI-related technologies we measure, though most very large firms reported at least some AI use. Weighted by employment, average adoption was just over 18\%. AI use in production, while varying considerably by industry, was found in every sector of the economy and clustered with emerging technologies, such as cloud computing and robotics. Among dynamic young firms, AI use was highest alongside more-educated, more-experienced, and younger owners, including owners motivated by bringing new ideas to market or helping the community. AI adoption was also more common alongside indicators of high-growth entrepreneurship, including venture capital funding, recent product and process innovation, and growth-oriented business strategies. Early adoption was far from evenly distributed: a handful of ``superstar" cities and emerging hubs led startups' adoption of AI. These patterns of early AI use foreshadow economic and social impacts far beyond this limited initial diffusion, with the possibility of a growing ``AI divide" if early patterns persist.

Keywords: Artificial Intelligence, Machine Learning, Adoption, Diffusion, Innovation, Entrepreneurship

JEL Classification: D22, M13, M21, O32, O33, O51, R10

Suggested Citation

McElheran, Kristina and Li, J. Frank and Brynjolfsson, Erik and Kroff, Zachary and Dinlersoz, Emin and Foster, Lucia and Zolas, Nikolas Jason, A.I. Adoption in America: Who, What, and Where (December 22, 2023). Journal of Economics and Management Strategy, Forthcoming , Available at SSRN: https://ssrn.com/abstract=4673528

J. Frank Li

Stanford University ( email )

Stanford, CA 94305
United States

Erik Brynjolfsson

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Stanford ( email )

366 Galvez St
Stanford, CA 94305
United States

HOME PAGE: http://brynjolfsson.com

Zachary Kroff

U.S. Census Bureau

4600 Silver Hill Road
D.C., WA 20233
United States

Emin Dinlersoz

Center for Economic Studies - US Census Bureau ( email )

4600 Silver Hill Road
Washington, DC 20233
United States

Lucia Foster

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

4700 Silver Hill Road
Washington, DC 20233
United States

Nikolas Jason Zolas

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

4700 Silver Hill Road
Washington, DC 20233
United States

University of California, Davis ( email )

One Shields Avenue
Apt 153
Davis, CA 95616
United States

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