Reducing carbon emission at the corporate level: Does artificial intelligence matter?

Abstract

As one of the primary objectives of energy transition, carbon emission (CE) reduction is directly related to the preservation of the ecological system as well as the welfare of humanity. However, most countries still face the dilemma of insufficient driving force for technological innovation and environmental inefficiency, resulting in the failure to achieve the emission reduction target as expected. Artificial Intelligence (AI), as a catalyst to promote a fresh cycle involving advances in technology along with industrial revolution, provides novel solutions for CE reduction and attracts the attention of many scholars. However, the impact of AI adoption on enterprise carbon emissions (CEs) has not been fully studied. This study addresses the existing research void by investigating the correlation between AI adoption and CEs of Chinese A-share listed companies from 2009 to 2021. Using panel fixed-effects regression analysis, it is found that AI adoption has a significant negative impact on CEs, a finding which stays robust after controlling for potential endogeneity issues. Heterogeneity analyses indicate that AI adoption has a more significant CE suppression effect in non-polluting, non-high-tech, and capital-intensive industries. In addition, AI adoption is more effective in suppressing CEs in regions with non-state-owned firms or strict environmental regulations. Mechanism analysis reveal that the increase in CEs is attributed to the increase in R&D expenditures and inputs due to scale expansion and the rebound effect due to efficiency improvement. The decrease in CEs, on the other hand, is attributed to the improvement in managerial and financial capabilities and the facilitation of information sharing.