Impact of artificial intelligence technology applications on corporate energy consumption intensity

Abstract

Artificial intelligence (AI), as a new technology, not only revolutionizes economic development, but also provides an opportunity for environment governance. Extant studies primarily explore the environmental performance of AI from a macro perspective, while evidence on how AI technology applications affect firms’ energy-saving behavior is scarce. Employing Python technology to recognize AI-related keywords in the annual reports of listed enterprises and adopting data on corporate energy consumption from 2011 to 2020, we explore the impact of AI on corporate energy consumption intensity (CECI) and its mechanisms. We observe that AI technology applications reduce CECI. After a range of robustness tests, the conclusions are still solid. The mechanism analysis reveals that AI cuts CECI through spurring firm green innovation, stimulating firms to introduce new equipment, and reducing firms’ internal management costs. Heterogeneity analysis reveals that this negative impact is more prominent for SOEs and private enterprises’ energy intensity; we also find that this effect is more pronounced for high-tech industry enterprises and high-polluting enterprises. Our findings provide micro evidence for policymakers to reduce corporate energy intensity and realize energy conservation and emission abatement targets.