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Artificial Intelligence Technology and Regional Carbon Emission Performance: Does Energy Transition or Industrial Transformation Matter?

Author

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  • Fang Qu

    (School of Economics, Xihua University, Chengdu 610039, China)

  • Wensen She

    (School of Economics, Xihua University, Chengdu 610039, China)

Abstract

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.

Suggested Citation

  • Fang Qu & Wensen She, 2025. "Artificial Intelligence Technology and Regional Carbon Emission Performance: Does Energy Transition or Industrial Transformation Matter?," Sustainability, MDPI, vol. 17(5), pages 1-31, February.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:5:p:1844-:d:1596823
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