Artificial Intelligence Adoption and Corporate Biodiversity Concern: Evidence from Chinese Listed Firms

Abstract

Given the growing ecological and economic risks posed by biodiversity loss, this study uses panel data on Chinese A-share listed firms from 2010 to 2023 and employs a debiased machine learning approach to empirically investigate the impact of artificial intelligence (AI) adoption on corporate biodiversity concern (CBC) and its underlying mechanisms. The results indicate that AI adoption significantly increases CBC. Mechanism analysis indicates that AI adoption enhances CBC by strengthening green knowledge management capabilities, improving green innovation capability, and increasing analyst coverage. Further analysis of moderating effects shows that the positive impact of AI adoption on CBC is more pronounced for firms facing higher climate risk, in regions with stronger environmental regulatory intensity, and among firms with higher levels of digital transformation. This study provides empirical evidence on the role of digital technologies in advancing corporate biodiversity governance.