The effects of artificial intelligence and environmental pollution on green growth in China

Achieving sustainable economic development requires policies that reconcile growth with environmental protection. This study examines how artificial intelligence (AI) and environmental regulation (ER) affect green growth (GG) in China, controlling for fiscal policy, human capital and urbanization. Using panel data for 30 provinces over 2011–2020, we construct a composite GG index with the entropy method and estimate effects with the Method of Moments Quantile Regression (MMQR), complemented by a panel quantile Granger causality test. AI and ER both raise GG at the lower, middle and upper quantiles. The AI effect grows across quantiles, while the ER effect is small and declines slightly. Fiscal policy, human capital and urbanization also promote GG, and linear panel estimates confirm these results. The AI effect depends on adoption level: it is positive in high-AI provinces but negative in low-AI provinces. The causality test indicates that all five variables Granger-cause GG across most quantiles. These findings support combining AI adoption with environmental regulation, alongside targeted support for low-adoption provinces.