Exploring the role of artificial intelligence as a catalyst for energy technology innovation

Mingxing Shao, Lei Wen, Sifei Li and Binyue Huang

Energy Economics, 2025, vol. 147, issue C

Abstract: Artificial intelligence (AI) has a strong spillover effect and acts as an essential propellant for advancements in technology and development. Using A-share listed enterprises between 2007 and 2022 as the sample, we assess the influence of AI on energy technology innovation (ETI). Our findings highlight that AI can promote ETI primarily by improving the human capital structure and encouraging enterprises to increase research and development (R&D) expenditure. This effect is more pronounced in enterprises with low-carbon transition strategy, those located in regions with abundant resource endowments, and those situated in clean energy base areas. Moreover, the study reveals that AI can positively affect ETI and contribute to enhanced enterprise environmental performance. The findings provide more thorough understanding of the critical role of AI in energy and innovation, offering practical recommendations for enterprises to leverage AI in boosting energy efficiency and lowering pollutant emissions, thereby aligning with as well as encouraging the attainment of carbon neutrality and peaking targets set by China.

Keywords: Artificial intelligence; Energy technology innovation; R&D expenditure; Human capital structure (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:147:y:2025:i:c:s0140988325004025

DOI: 10.1016/j.eneco.2025.108578

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