This paper reviews firm-level data on artificial intelligence (AI) and the emerging evidence on AI’s economic effects. It argues that measurement is central: different AI data sets capture different objects, including invention versus use; internal capability building versus outsourcing; and realized activity versus investor perceptions, and can therefore lead to different conclusions. The paper develops a framework for choosing among these measures and surveys available data sources on firm AI efforts. It synthesizes evidence on AI’s effects on firm growth, valuation, productivity, risk, labor, competition, financial markets, and applications. The paper concludes by suggesting some ideas for future research.

Using U.S. Census firm-worker data, I document that firms' financial distress has an economically important effect on employee departures to entrepreneurship. The impact is amplified in the high-tech and service sectors, where employees are key assets. In states with enforceable noncompete contracts, the effect is mitigated. Compared to typical entrepreneurs, distress-driven entrepreneurs are high-wage workers who found better firms, as measured by jobs, pay, and survival. Startup jobs compensate for 33% of job losses at the constrained incumbents. Overall, the financial inability of incumbent firms to pursue productive opportunities increases the reallocation of economic activity into new firms.

This paper offers the first study of how changes in corporate R&D investment affect labor mobility. We show that increases in R&D spur employee departures to join start-ups’ founding teams. This appears to reflect employees taking the ideas, skills, or technologies created through the R&D process but not especially valuable to the R&D-investing firm to start-ups. The employee-founded start-ups tend to be outside the R&D-investing employer’s industry, suggesting that the underlying ideas would impose diversification costs on the R&D-investing firm. The start-ups are more likely to be VC backed, high tech, and high wage, pointing to substantial spillover benefits.

How does access to public equity markets affect the human capital of IPO filing firms? While IPO filing firms have high average wages and limited industrial diversification, a successful IPO increases departures of high-wage employees to startups and triggers industrial diversification through employment growth in non-core industries. Surprisingly, IPOs do not significantly affect the earnings growth of pre-IPO workers. Instead, post-IPO hires receive larger earnings increases upon joining. Overall, going public has a significant effect on a firm’s workforce and labor reallocation across firms.

Using a novel data set of over 3,500 public and private firms, we construct the network of executive and director connections prior to the 1929 financial market crash. We find that more connected firms have 17% higher 10-year survival rates. Consistent with a working capital channel, the results are strongest for small, private, cash-poor firms, and firms located in counties with high bank suspension rates. Moreover, connections to cash-rich firms that increase accounts receivable matter the most. Our results suggest that network connections can play a stabilizing role during a financial crisis by easing the flow of capital to constrained firms.

We examine innovation following the Great Depression using data on a century’s worth of U.S. patents and a difference-in-differences design that exploits regional variation in the crisis severity. Harder-hit areas experienced large and persistent declines in independent patenting, mostly reflecting the disruption in access to finance during the crisis. This decline was larger for young and inexperienced inventors and lower-quality patents. In contrast, innovation by large firms increased, especially among young and inexperienced inventors. Overall, the Great Depression contributed to the decline in technological entrepreneurship and accelerated the shift of innovation into larger firms.

We evaluate the impacts of tax policy on asset returns using the U.S. municipal bond market. In theory, tax-induced ownership segmentation limits risk sharing, creating downward-sloping regions of the aggregate demand curve for the asset. In the data, cross-state variation in tax privilege policies predicts differences in in-state ownership of local municipal bonds; the policies create incentives for concentrated local ownership. High tax privilege states have muni bond yields that are more sensitive to variations in supply and local idiosyncratic risk. The effects are stronger when local investors face correlated background risk and/or diminishing marginal nonpecuniary benefits from holding local assets.

We study the use and economic impact of AI technologies. We propose a new measure of firm-level AI investments using employee resumes. Our measure reveals a stark increase in AI investments across sectors. AI-investing firms experience higher growth in sales, employment, and market valuations. This growth comes primarily through increased product innovation. Our results are robust to instrumenting AI investments using firms' exposure to universities' supply of AI graduates. AI-powered growth concentrates among larger firms and is associated with higher industry concentration. Our results highlight that new technologies like AI can contribute to growth and superstar firms through product innovation.

This article studies how federal funding affects the innovation outputs of university researchers. We link person-level research grants from 22 universities to patents, publications, and career outcomes from the U.S. Census Bureau. We focus on the effects of large, idiosyncratic, and temporary cuts to federal funding in a researcher’s preexisting narrow field of study. Using an event study design, we document that these negative federal funding shocks reduce high-tech entrepreneurship and publications but increase patenting. The lost publications tend to be higher quality and more basic, whereas the additional patents tend to be lower quality, less general, and more often privately assigned. These federal funding cuts lead to an increase in private funding, which partially compensates for the decline in federal funding. Together with evidence from industry-university contracts, the results suggest that federal funding cuts shift university research funding from federal to private sources and lead to innovation outputs that are less openly accessible and more often appropriated by corporate funders.

Open banking (OB) empowers bank customers to share their financial transaction data with fintechs and other banks. New cross-country data shows 49 countries adopted OB policies, privacy preferences predict policy adoption, and adoption spurs fintech entry. UK microdata shows that OB enables: (i) consumers to access both financial advice and credit; (ii) SMEs to establish new lending relationships. In a calibrated model, OB universally improves welfare through entry and product improvements when used for advice. When used for credit, OB promotes entry and competition by reducing adverse selection, but higher prices for costlier or privacy-conscious consumers partially offset these benefits.