TY - JOUR
T1 - AI, ESG, and Energy Transition in Emerging Markets
T2 - A Multidimensional Analysis
AU - Chen, Diana
AU - Yu, Xiaohong
AU - Pardo-Piñashca, Eduardo
N1 - Publisher Copyright:
© 2026 ERP Environment and John Wiley & Sons Ltd.
PY - 2026
Y1 - 2026
N2 - As the global energy system shifts from fossil fuels to renewable sources, AI has become a crucial component of this transformation. This study explores the influence of AI on the energy transition (ET) in emerging markets from 1993 to 2019, focusing on the role of environmental, social, and governance (ESG) performance. The results are summarized as follows. First, AI accelerates ET, and this finding remains consistent after robustness checks and addressing potential endogeneity issues. Second, AI has an indirect effect on ET by enhancing environmental and social performance. Third, AI has a nonlinear impact on ET across different levels of governance. As governance performance overextends, the positive effect of AI on ET decreases. Fourth, the heterogeneity analysis reveals that the threshold effect of governance performance varies across different income levels. This study presents several recommendations for integrating AI into renewable energy development.
AB - As the global energy system shifts from fossil fuels to renewable sources, AI has become a crucial component of this transformation. This study explores the influence of AI on the energy transition (ET) in emerging markets from 1993 to 2019, focusing on the role of environmental, social, and governance (ESG) performance. The results are summarized as follows. First, AI accelerates ET, and this finding remains consistent after robustness checks and addressing potential endogeneity issues. Second, AI has an indirect effect on ET by enhancing environmental and social performance. Third, AI has a nonlinear impact on ET across different levels of governance. As governance performance overextends, the positive effect of AI on ET decreases. Fourth, the heterogeneity analysis reveals that the threshold effect of governance performance varies across different income levels. This study presents several recommendations for integrating AI into renewable energy development.
KW - ESG performance
KW - artificial intelligence
KW - emerging markets
KW - energy transition
KW - governance
UR - https://www.scopus.com/pages/publications/105033066697
U2 - 10.1002/sd.70959
DO - 10.1002/sd.70959
M3 - Article
AN - SCOPUS:105033066697
SN - 0968-0802
JO - Sustainable Development
JF - Sustainable Development
ER -