How Artificial Intelligence Empowers Regional Low-Carbon Transformation—From the Dual Perspectives of “Carbon Reduction” and “Efficiency Enhancement”

Artificial intelligence is a strategic technology driving the new round of technological revolution and industrial transformation, providing significant impetus for China's high-quality development. This paper employs a two-way fixed effects model and a mediation effect model to empirically analyze AI's impact on regional low-carbon transformation using provincial-level data from China between 2013 and 2022. The findings reveal that AI effectively curbs total carbon emissions while simultaneously boosting green total factor productivity. This conclusion remains robust across a series of stability tests. AI facilitates regional low-carbon transformation by enhancing energy efficiency, accelerating green technological innovation, and accelerating industrial upgrading. The study's conclusions offer significant policy implications for further advancing AI development, leveraging its role in regional emission reduction and efficiency gains, and accelerating high-quality economic development.

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Publication Details

Journal
Journal of Economics and Public Finance
Published
2025-09-25
DOI
https://doi.org/10.22158/jepf.v11n3p225
Primary Topic
Arctic and Russian Policy Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

How Artificial Intelligence Empowers Regional Low-Carbon Transformation—From the Dual Perspectives of “Carbon Reduction” and “Efficiency Enhancement”

Xifeng Jiang
Journal of Economics and Public Finance
Arctic and Russian Policy Studies
article

How Artificial Intelligence Empowers Regional Low-Carbon Transformation—From the Dual Perspectives of “Carbon Reduction” and “Efficiency Enhancement”

Xifeng Jiang
article en

Abstract

Artificial intelligence is a strategic technology driving the new round of technological revolution and industrial transformation, providing significant impetus for China's high-quality development. This paper employs a two-way fixed effects model and a mediation effect model to empirically analyze AI's impact on regional low-carbon transformation using provincial-level data from China between 2013 and 2022. The findings reveal that AI effectively curbs total carbon emissions while simultaneously boosting green total factor productivity. This conclusion remains robust across a series of stability tests. AI facilitates regional low-carbon transformation by enhancing energy efficiency, accelerating green technological innovation, and accelerating industrial upgrading. The study's conclusions offer significant policy implications for further advancing AI development, leveraging its role in regional emission reduction and efficiency gains, and accelerating high-quality economic development.

Journal of Economics and Public FinanceVol. 11(3)
Openalex Percentile: Top 65%
Arctic and Russian Policy Studies
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How Artificial Intelligence Empowers Regional Low-Carbon Transformation—From the Dual Perspectives of “Carbon Reduction” and “Efficiency Enhancement” — Xifeng Jiang · Journal of Economics and Public Finance (2025) | TGRS Research Map | TGRS