Harnessing AI for renewable energy transition: Threshold effects on China’s economic growth

Under the guidance of the Paris Agreement, countries worldwide have accelerated the adoption of clean energy technologies and promoted the use of renewable energy to achieve emissions reduction targets. China has set ambitious goals of peaking carbon emissions by 2030 and achieving carbon neutrality by 2060, supported by substantial investments across the renewable energy industry chain. However, the significant upfront costs and extended payback periods have raised concerns about potential impacts on economic growth. Simultaneously, advancements in artificial intelligence (AI) offer critical support for energy transitions by improving energy efficiency and optimizing smart grid systems. This study employs panel data from 31 Chinese provinces between 2000 and 2022. It develops a dynamic panel threshold model that accounts for cross-sectional dependence to examine the nonlinear effects of renewable energy consumption on economic growth. The findings reveal that when a province's GDP is below RMB 2,037.37 billion, renewable energy consumption exerts a significant negative impact on economic growth. In contrast, once GDP surpasses this threshold, renewable energy consumption significantly enhances economic growth. Furthermore, the study demonstrates that higher levels of AI development amplify the positive impact of renewable energy consumption on economic growth. These results highlight the critical role of the synergy between AI technologies and renewable energy consumption in driving high-quality economic development. Policy recommendations include accelerating the application of AI in the energy sector and advancing the coordinated development of green energy systems and economic transformation.