Can artificial intelligence help companies curb carbon emissions?
Dan Wang et al.
Abstract
Purpose The purpose of this paper is to examine the impact of artificial intelligence (AI) on firm carbon emissions. Further, we attempt to estimate the presence of a nonlinear relationship between AI and corporate carbon emissions across industries. In addition, our paper aims to understand the role that green innovation plays in the reduction of carbon emissions by firms. Design/methodology/approach Our research takes advantage of detailed data on enterprise carbon emissions from 2013 to 2022 in China. We assessed the level of AI information in the annual report of companies through a textual analysis of AI keywords. Using a panel OLS regression, we investigate the effect of enterprise adoption of AI on carbon emissions. Findings In an examination of 2,137 Chinese public listed companies between 2013 and 2022, we found a significant relationship between AI technology and corporate carbon emissions. More importantly, we find that this relationship is nonlinear (inverted U-shape). Furthermore, we find that green innovations play a partial mediating role in this process. Finally, we show that firms in labor-intensive industries, with heavy pollution, and in the eastern region show a more prominent inverted U-shaped relationship. Originality/value Our paper fills a literature gap by examining the nonlinear relationship between AI and corporate carbon emissions across industries. In addition, we are interested in understanding the role that green innovation plays in firms' efforts to reduce carbon emissions. Findings in our paper could have important policy and practice implications for academics, policymakers and investors.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.