The impact of artificial intelligence (AI) technology on carbon emissions performance is considered to be a double-edged sword. The debate is aided by this paper’s use of data from 278 Chinese cities from 2009 to 2019 based on the two-way fixed effects, instrumental variables (IVs), spatial Durbin (SDM), mediation effect, and moderating effect model. We find that AI technology not only increases the carbon emission scale, but also has an undesirable impact on carbon emission efficiency, which indicates that the use of AI technology currently does not necessarily improve carbon emission performance. Moreover, AI technology does have the potential to reduce the carbon emission scale and improve carbon emission efficiency through energy transition, though this potential is not reflected in industrial transformation. Finally, the impact of AI technology on carbon emission performance is worsened by the energy industry’s investment, suggesting that current investments are not being used to enhance AI applications in the field of energy. This study shows that the role of energy transition is crucial if current AI technologies are to achieve a ‘decarbonization effect’, and that energy industry investments need to be focused on the penetration of AI technologies to realize its positive effect.

Based on the spillover index and an improved spillover asymmetric measure method, this paper studies the volatility spillover and its asymmetric effect between crude oil and agricultural commodity futures in pre- and post-outbreak of COVID-19. We find that the total volatility spillover is higher with pre-outbreak of COVID-19. In addition, the volatility spillover caused by China’s crude oil is more prominent than international crude oil around the COVID-19, which highlights the necessity of risk control through the establishment of an energy financial market in China. Finally, although the asymmetric effect of volatility spillover has always existed, crude oil was less impacted by good news post-outbreak of COVID-19, indicating that the outbreak of COVID-19 makes assets dominated by commodity attributes more sensitive to bad news. These findings are beneficial for investors to establish a cross-sector risk hedging portfolio, and provide empirical evidence for policymakers to ensure energy and food security.