Impacts of Artificial intelligence and Technology on Productivity in Green Development: A Study of Chinese Provinces

In response to increasing environmental pressures and the global demand for sustainable resource management, green development has become a key pathway for optimizing economic structures, particularly in the context following the 2012 Rio+20 Conference. This study examines the impact of Artificial Intelligence (AI), Industrial Structure Upgrading (ISU), Operational Expenses (OPE), and Technological Innovation (TI) on Green Total Factor Productivity (GTFP), utilizing an unbalanced panel dataset from 30 Chinese provinces spanning the period 2011–2020. The empirical results indicate that AI exerts a positive and statistically significant effect on GTFP, with a coefficient of 0.052, suggesting enhanced efficiency and resource optimization. ISU similarly demonstrates a positive effect, with a coefficient of 0.044, reflecting the role of structural improvements in promoting environmentally efficient production. TI also contributes positively to GTFP, with a coefficient of 3.83, underscoring the importance of innovation-driven sustainable growth. In contrast, OPE shows a significant negative influence, with a coefficient of -0.054, indicating that increased operational costs impede productivity improvements. These findings highlight the necessity of encouraging technological upgrading, innovation development, and AI adoption, alongside the effective management of operational expenditures, to support green and sustainable economic advancement across provinces.