Abstract 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. (JEL D22, E22, J23, J24, L11, O33)
Tania Babina (Sun,) studied this question.