Artificial intelligence, green transition and green total factor productivity in enterprises

作者：Huan Li · 发表于：Scientific Reports · 年份：2025 · DOI：10.1038/s41598-025-18878-y · 被引用次数：12 · 研究领域：Energy, Environment, Economic Growth、Environmental Sustainability in Business、Sustainable Supply Chain Management

Coupled with swift advancement of artificial intelligence (AI), relationship between AI and an enterprise's green total factor productivity (GTFP) is receiving increasing attention. This study conducts an empirical analysis of the relationship between AI and GTFP in Chinese enterprises over the period 2007-2022. The results demonstrate that AI development significantly enhances GTFP, with enterprise green transformation serving as a key mechanism. Further decomposition of GTFP indicates that AI contributes to improvements in both green technical efficiency and green technological progress. The findings also reveal significant heterogeneity across different types of AI technologies: while computer vision and machine learning have a strong positive impact on GTFP, logic-based AI does not exhibit a meaningful effect. Moreover, there is notable heterogeneity across regions and the positive effect of AI on GTFP is more pronounced in western regions of China. In addition, the impact of AI varies by firm characteristics-such as whether firms are labor-intensive, technology-intensive, or capital-intensive.