Does artificial intelligence reduce energy intensity in manufacturing? Evidence from country-level data

Chao Zhong, Hongbo Cai, Shuai Fang, Rui Xue and Yuli Shan

Energy Economics, 2025, vol. 149, issue C

Abstract: This paper examines the impact of artificial intelligence (AI) technology on the energy intensity of manufacturing industries using cross-country analysis. The findings reveal that AI adoption significantly reduces energy intensity in manufacturing, underscoring its potential for energy savings. To mitigate endogeneity concerns, the Bartik instrument variable method is used and the key findings are held. We further document substantial heterogeneity across economic contexts. Specifically, in high-income countries and developed economies, especially in G7 and European Union countries, AI application does not significantly reduce energy intensity. However, in middle-income countries and emerging economies, particularly in European emerging markets, AI adoption leads to a substantial decrease in energy intensity. Furthermore, we reveal that AI enhances energy efficiency through technological advancement and application dissemination. Based on these findings, we offer practical policy recommendations for promoting the sustainable development of the AI-energy intensity nexus in manufacturing.

Keywords: Artificial intelligence; Energy intensity; Manufacturing; R&D; Technology application (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:149:y:2025:i:c:s0140988325006115

DOI: 10.1016/j.eneco.2025.108784

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