<scp>AI</scp> , <scp>ESG</scp> , and Energy Transition in Emerging Markets: A Multidimensional Analysis

ABSTRACT 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.

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Publication Details

Journal
Sustainable Development
Published
2026-03-16
DOI
https://doi.org/10.1002/sd.70959
Primary Topic
Energy, Environment, Economic Growth
Type
article
Field-Weighted Citation Impact
0.00
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article

AI , ESG , and Energy Transition in Emerging Markets: A Multidimensional Analysis

Xiaohong Yu, Diana Chen, Eduardo Pardo‐Piñashca
Sustainable Development
Energy, Environment, Economic Growth
article

AI , ESG , and Energy Transition in Emerging Markets: A Multidimensional Analysis

Xiaohong Yu, Diana Chen, Eduardo Pardo‐Piñashca
article en

Abstract

ABSTRACT 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.

Sustainable Development
Beijing Institute of Technology (CN), Pontificia Universidad Católica del Perú (PE)
Affordable and clean energy
Openalex Percentile: Top 23%
Energy, Environment, Economic Growth
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