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Back to papersAbstract Summary Main Finding Notes NBER WP 31788 (2023); published in J. Econ & Mgmt Strategy
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
[Claude classification]: NBER WP 31788 (October 2023). The paper explicitly states it does not aim to establish causal relationships between firm characteristics and adoption, nor between adoption and firm growth (Section 4.1). AI-related technologies measured include: automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition. The study links the 2018 ABS to the Longitudinal Business Database (LBD) which provides panel data on employment and revenue from firm birth through 2017. Sample includes 447,000 firms (baseline) representing over 4 million firms when weighted; detailed startup analysis uses 75,000 young firms. Geographic analysis focuses on Core-Based Statistical Areas (CBSAs). Revenue growth analysis uses log-difference measure averaged over 3-year windows.
AI Adoption in America: Who, What, and Where
McElheran, Li, Brynjolfsson, Kroff, Dinlersoz, Foster, Zolas
2023NBER Working Paper Series / Journal of Economics and Management Strategy38 citations
Adoption / usageInterdisciplinary
AI AdoptionMachine LearningAutomation / RobotsComputer Vision / Image AIFinanceDeveloping economiesHuman-AI collaborationAugmentation vs. substitution
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, nevertheless 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 moreeducated, 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.
McElheran et al. analyze the 2018 Annual Business Survey of 850,000 US firms linked to administrative employment and revenue data to document patterns of AI adoption across industries, firm sizes, geographies, and among startups with detailed owner and organizational characteristics.
As of 2017, fewer than 6% of US firms used AI-related technologies, though employment-weighted adoption was 18%; AI use was concentrated among very large firms, clustered with cloud computing and robotics, and among startups was strongly associated with venture capital funding, advanced owner education, process innovation, patent ownership, and growth-oriented strategies.
Secondary Datasets
Business Dynamics Statistics (BDS) for weighting
- Key Methods
- Descriptive analysis of nationally representative firm survey linked to administrative employment and revenue data; linear probability models with rich firm-level covariates including owner characteristics, startup financing, innovation strategies, and geography
- Sample Period
- 2017-2018
- Geographic Coverage
- US
- Sample Size
- 447,000 firms in baseline sample (weighted to represent over 4 million US employer firms); 75,000 startups for detailed organizational analysis; 573,000 firms in full ABS-LBD linked sample
- Level of Analysis
- Firm, Industry, Region
- Occupation Classification
- None
- Industry Classification
- NAICS