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How can artificial intelligence technology applications accelerate energy innovation in China? Evidence from provincial regional data

  • Qing Zhu
  • , Jianhua Che
  • , Shan Liu
  • , Liangzheng Wu
  • , Jigang Zhang
  • , Yuze Li
  • Shaanxi Normal University
  • Xi’an Jiaotong University
  • Ltd
  • China Southern Power Grid
  • Boston University

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

In light of the rapid proliferation of artificial intelligence (AI) technology applications in China, coupled with the nation's persistent increase in energy consumption, there is an imperative for China to undertake a thorough examination of the influence of AI technology applications on energy efficiency. This research aims to identify pathways for balancing energy efficiency improvements with low-carbon transitions to enhance energy security. Existing studies have explored the impact on energy efficiency during the development of AI technology applications narrowly. To address this gap, this paper analyzes China's provincial energy efficiency from 2010 to 2019 from three aspects: energy consumption, desired output, and undesired output. Empirical analysis shows AI technology applications can significantly boost energy efficiency by cutting energy consumption and undesired outputs, helping improve energy security. However, in the short term, these applications show no significant impact on macroeconomic output. Concurrently, Urbanization level exerts a favorable moderating effect on this process. Furthermore, AI technology applications impacts on energy efficiency are more pronounced in low-energy consuming regions and in the South. These findings offer in-depth insights into how AI technology applications enhance energy security through energy efficiency and pollution reduction and provide guidance for improving energy policies and enabling scientific decision-making in different Chinese regions.

Original languageEnglish
Pages (from-to)484-502
Number of pages19
JournalEconomic Analysis and Policy
Volume87
DOIs
StatePublished - Sep 2025
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Artificial Intelligence
  • Data envelopment analysis modeling
  • Energy consumption
  • Energy efficiency
  • Pollution emissions

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