Artificial Intelligence Innovation and Regional Water Inequality in China: Evidence from Provincial AI Patenting

Water inequality arises when regional water use is disproportionate to local socioeconomic and resource conditions. Yet, little is known about whether artificial intelligence (AI) technological innovation is associated with this mismatch. Using panel data for 31 provincial-level regions in mainland China from 2015 to 2024, this study examines the relationship between AI technological innovation and regional water inequality, measured from a water footprint perspective. The annual number of patent applications related to AI is used to measure regional AI technological innovation, and an instrumental variable generalized method of moments (IV-GMM) approach is employed to address potential endogeneity. The estimates show that AI technological innovation is significantly associated with lower regional water inequality: a 1% increase in AI patenting is associated with an approximately 0.249% decrease in the water inequality index. This result remains robust after adding further controls and applying alternative instrumental variable estimators. The quantile estimates remain negative across the conditional distribution of water inequality, although formal tests do not indicate statistically significant differences. AI technological innovation is also positively associated with financial development and industrial structure upgrading, providing evidence consistent with their potential roles as channels. The association is statistically significant in provinces with lower tax burdens and higher levels of industrialization, although formal differences between groups are statistically significant only for tax burden. These findings suggest that AI innovation policies may be more effective when combined with practical applications in water governance and adapted to local fiscal and industrial conditions.