Corporate sustainable development effects of the artificial intelligence pilot zone policy: evidence from China based on double machine learning
Year: 2026
Type: article
Abstract: Introduction As digital transformation becomes increasingly intertwined with green development, whether the artificial intelligence pilot zone (AIPZ) policy improves corporate sustainable development performance warrants empirical examination. Methods Using Chinese A-share listed firms from 2009 to 2023, we treat the establishment of AIPZs as a quasi-natural experiment and apply double machine learning to estimate the policy effect. Results The AIPZ policy significantly improves corporate sustainable development performance, and the result is robust across alternative specifications and tests. Decomposition analysis shows improvements in environmental performance, the joint development level, and the balance between economic and environmental performance, despite a decline in return on assets. Mechanism tests point to green innovation, lower agency costs, and human capital upgrading as potential channels. The effect is stronger among non-state-owned enterprises, firms outside heavily polluting industries, and high-tech firms. Discussion These findings suggest that governance arrangements, environmental constraints, and technological capabilities shape firms’ responses to the policy. They provide firm-level evidence on how place-based artificial intelligence policy may support green corporate transformation.
Authors: Qinfeng Gao, Wenxiu Hu, Xin Wang, Yazhou Liu
Institution: Xi'an University of Technology
Subfield: Strategy and Management
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W7221783189