Towards carbon neutrality: The effects of artificial intelligence on carbon neutrality technology innovation

作者：Dan Ma, Fang Xiao, Chien‐Chiang Lee · 发表于：Energy · 年份：2025 · DOI：10.1016/j.energy.2025.139583 · 被引用次数：4 · 研究领域：COVID-19 impact on air quality、Integrated Energy Systems Optimization、Maritime Transport Emissions and Efficiency

As a pivotal technological advancement, artificial intelligence (AI) is witnessing increasing integration into carbon neutrality initiatives. However, there is a lack of research on the potential impact of AI on carbon neutrality technology innovation (CNTI). This paper, for the first time, combines the Large Language Model and patent abstracts to accurately identify CNTI. This study systematically explores how AI impacts enterprises while examining its fundamental mechanisms. The principal conclusions derived from this study are summarized below: firstly, AI significantly promotes the CNTI of enterprises, especially in zero-carbon technologies. Secondly, AI can effectively promote CNTI of enterprises by enhancing knowledge absorption capacity, green innovation quality, and collaborative innovation level. Thirdly, the promoting effect of AI is more effective for technology-intensive industry enterprises, heavy pollution industry enterprises, high market competition enterprises, and low financing-constrained enterprises. Fourthly, an intelligent application has the most significant impact on CNTI. At last, we put forward policy recommendations to leverage AI to achieve the “dual carbon” goal.