Artificial Intelligence and Corporate Sustainability Disclosure: Evidence from Corporate Climate Risk Disclosure in China
Abstract
As artificial intelligence becomes more deeply embedded in corporate sustainability governance, it remains unclear whether public policies centered on AI development are linked to changes in corporate sustainability disclosure. Focusing on corporate climate risk disclosure as an important dimension of sustainability disclosure, this study examines how China’s National Artificial Intelligence Innovation and Development Pilot Zone policy, referred to as the AI Pilot Zone policy, is associated with firms’ disclosure of climate-related risks. Using Chinese A-share listed firms from 2014 to 2023 and a multi-period difference-in-differences approach, we find that the AI Pilot Zone policy is associated with higher levels of corporate climate risk disclosure. A series of robustness checks further confirms the stability of this finding. Mechanism analysis provides suggestive evidence consistent with three channels: climate-related information-processing capability, climate risk governance capability, and external monitoring pressure. The subsample estimates reveal that the association is more pronounced among firms under greater environmental pressure, firms with higher levels of institutional ownership, and firms whose managers exhibit stronger green awareness. Additional analysis suggests that climate risk disclosure is positively associated with ESG performance, especially environmental and governance performance. This study contributes firm-level empirical evidence on the association between AI-oriented public policies and corporate climate risk disclosure, while highlighting the need to distinguish disclosure improvement from substantive sustainability transformation.
Fields of Study & Subjects
Corporate Social Responsibility Reporting
Auditing
Earnings Management
Governance
Impact of AI and Big Data on Business and Society
Publication details
- Journal / source
- Sustainability
- Publisher
- MDPI AG
- Volume
- 18
- Issue
- 14
- Pages
- 7313–7313
- Publication date
- 17 July 2026
- Language
- EN