Examining the role of artificial intelligence in advancing pollution reduction strategies

Abstract

Abstract This study is based on the panel data from 2006 to 2020 to explore the relationship between artificial intelligence (AI) and pollution emission. The study demonstrates a notable and statistically significant reduction in pollution emission intensity attributable to AI. This finding is robust, holding up under various sensitivity analyses and addressing endogeneity using instrumental variable techniques. The mechanism analysis reveals that AI's role in decreasing emissions primarily arises from three factors: the promotion of technological innovation, increased investment in emission reduction technology, and the replacement of low‐skilled labor with more efficient alternatives. We also find more substantial environmental benefits in areas with stricter environmental regulations and higher initial levels of pollution. Additionally, AI is shown to facilitate a symbiotic relationship between economic growth and environmental management. This research provides both empirical evidence and theoretical insights that reinforce the essential role of AI in driving green transformations, process upgrades, and high‐quality development. It situates these advancements within the broader context of the interplay between artificial intelligence, environmental sustainability, and economic progression.