Artificial intelligence, industrial structure optimization, and CO₂ emissions

The carbon-reducing effects of artificial intelligence (AI) will be a critical means of achieving carbon peak and carbon neutrality in China. However, in order to efficiently harness the power of AI, the relationship between AI and carbon reduction needs to be fully understood. In this study, we systematically investigated the impacts and mechanisms of action of AI on CO₂ emissions by constructing econometric models using dynamic panel data from 30 provinces in mainland China from 2006 to 2019. The empirical results show that AI significantly reduces CO₂ emissions. Further mediation effect tests found that in the western region, there are mediation effects of the quantity and quality of industrial structure advancedization and industrial structure ecology, while the mediation effect of industrial structure rationalization is not significant. In the eastern and central regions, the mediating effect of the quantity of industrial structure advanced is not significant, while the mediating effect of the quality of industrial structure advanced, industrial structure rationalization, and industrial structure ecology all exist. Our work provides evidence to support that AI reduces CO2 emissions in various regions of China. This can help regions formulate appropriate policies to promote the synergistic development of AI and the "dual-carbon" goal.