The influence of AI application on carbon emission intensity of industrial enterprises in China

As a critical aspect of the industry 4.0 era, the application of artificial intelligence (AI) is significant to environmental governance. It serves as a crucial driving force in assisting enterprises in the transition toward low-carbon practices. This paper examines China's A-share industrial enterprises from 2011 to 2022, constructs and trains a word vector model to extract AI-related terms, and the impact of AI applications on the carbon emission intensity of these enterprises is investigated. The findings reveal that enhancing the level of AI application can effectively decrease carbon emission intensity. Specifically, a 1% increase in AI application leads to a reduction of 0.0395% in carbon emission intensity. Further analysis indicates that enterprises can diminish their carbon emission intensity by the optimization of supply chain and green technology innovation. Heterogeneity analysis suggests that utilizing AI is beneficial for reducing the carbon emission intensity of manufacturing, high-tech, and high-pollution enterprises. The results of this study enrich the micro-level research on the relationship between AI and carbon emission intensity, offering valuable insights for enterprises aiming to achieve sustainable development.

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Publication Details

Journal
Scientific Reports
Published
2025-04-12
DOI
https://doi.org/10.1038/s41598-025-97110-3
Citations
14
Primary Topic
Energy, Environment, Economic Growth
Type
article
Field-Weighted Citation Impact
43.84
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article

The influence of AI application on carbon emission intensity of industrial enterprises in China

Zhidong Liao, Lu Yao
14 citations
Scientific Reports
Energy, Environment, Economic Growth
43.84
article

The influence of AI application on carbon emission intensity of industrial enterprises in China

Zhidong Liao, Lu Yao
article en
14 citations

Abstract

As a critical aspect of the industry 4.0 era, the application of artificial intelligence (AI) is significant to environmental governance. It serves as a crucial driving force in assisting enterprises in the transition toward low-carbon practices. This paper examines China's A-share industrial enterprises from 2011 to 2022, constructs and trains a word vector model to extract AI-related terms, and the impact of AI applications on the carbon emission intensity of these enterprises is investigated. The findings reveal that enhancing the level of AI application can effectively decrease carbon emission intensity. Specifically, a 1% increase in AI application leads to a reduction of 0.0395% in carbon emission intensity. Further analysis indicates that enterprises can diminish their carbon emission intensity by the optimization of supply chain and green technology innovation. Heterogeneity analysis suggests that utilizing AI is beneficial for reducing the carbon emission intensity of manufacturing, high-tech, and high-pollution enterprises. The results of this study enrich the micro-level research on the relationship between AI and carbon emission intensity, offering valuable insights for enterprises aiming to achieve sustainable development.

Scientific ReportsVol. 15(1)
Shanghai Ocean University (CN)
Openalex Percentile: Top 0%
Energy, Environment, Economic Growth
43.84
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The influence of AI application on carbon emission intensity of industrial enterprises in China — Zhidong Liao, Lu Yao · Scientific Reports (2025) | TGRS Research Map | TGRS