中国
强度(物理)
发射强度
碳纤维
业务
计算机科学
材料科学
地理
物理
光电子学
算法
考古
量子力学
光致发光
复合数
标识
DOI:10.1038/s41598-025-97110-3
摘要
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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