Value effect of AI innovation zones: Green premium and cost reduction pathways in environmental disclosure

As artificial intelligence drives the technological revolution, understanding its impact on corporate non-financial governance is essential. Using unbalanced panel data of China’s A-share listed firms, in this study, we employ a multi-period difference-in-differences (DID) model to examine the impact of the Artificial Intelligence Innovation and Development Pilot Zones (AIIDPZ) on corporate environmental disclosure quality, treating the policy rollout as a quasi-natural experiment. We find that the establishment of AIIDPZ significantly elevates the quality of environmental information disclosure. This finding remains robust after a series of tests, including propensity score matching-DID, placebo tests, and corrections for potential biases in two-way fixed effects models. Moreover, AIIDPZ enhances environmental information disclosure quality by improving green total factor productivity and reducing R&D costs. Heterogeneity analysis indicates that larger firms, newer firms, highly competitive industries, and firms facing higher financing constraints benefit most from the establishment of AIIDPZ. Government subsidies and organizational inertia further amplify the impact of AIIDPZ on corporate environmental information disclosure. This study contributes empirical evidence on the micro-level environmental consequences of AI industrial policies and offers policy implications for promoting green development through digital intelligence.