Jump Starting the AI Engine: The Complementary Role of Data and Management Practices

Abstract

Artificial intelligence is transforming business and society, but evidence that AI is boosting productivity is limited. To address this gap, I construct measures of AI investment for a large longitudinal sample of publicly-traded U.S. firms, as well as their data and management practices. I find that the average effects of AI investment on the firms’ productivity and stock market performance are noisy. However, long-differences regressions suggest that the benefits of AI become evident following an implementation lag period and instrumental variable regressions suggest a strong and sizeable positive impact. I also find significant heterogeneity across firms: The distribution of AI investment is skewed, and the impact of AI is only salient for a subgroup of distinctive firms. In particular, AI has a positive effect for firms with more intensive data or management practices, while the marginal effect of AI may not be statistically different from zero if the complementary practices are low. Furthermore, the performance gap persists and widens over time. These findings highlight the complementary role of data and management in leveraging AI investment to boost firms’ productivity and market value.

Keywords: Artificial Intelligence, Information Technology, Value of Data, Management Practice, Firm Performance, Complementarity

JEL Classification: D22, D24, E22, J24, L2, M1, M2, O33