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How does smart artificial intelligence influence energy system resilience? Evidence from energy vulnerability assessments in G20 countries

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  • Zhang, Yingnan
  • Hu, Wei
  • Tao, Yirui
  • Zhang, Bin

Abstract

Energy system resilience has become an escalating concern amid global economic developments, worsening climate change impacts, and localized regional conflicts. Artificial Intelligence (AI) has emerged as a pivotal tool for enhancing energy system resilience. This study delves into the association between AI and energy system resilience, investigating underlying mechanisms and heterogeneity using a fixed effects model applied to data from the Group of 20 (G20) economies. Energy system resilience can be characterized by a country's energy vulnerability. Our findings suggest that AI effectively mitigates energy vulnerability. Specifically, its impact is more pronounced in high carbon-emitting countries, while it plays a more limited role in highly developed economies. Conversely, in less economically developed countries, AI adoption may exacerbate energy vulnerability. Through mediation analysis, we validate the role of AI in fostering industrial structural transformation and upgrading. However, the direct impact of industrial structure on energy vulnerability was statistically insignificant, warranting further investigation. These results underscore AI's efficacy in reducing energy vulnerability and provide strategic insights for addressing global energy challenges and promoting sustainable development on a global scale.

Suggested Citation

  • Zhang, Yingnan & Hu, Wei & Tao, Yirui & Zhang, Bin, 2025. "How does smart artificial intelligence influence energy system resilience? Evidence from energy vulnerability assessments in G20 countries," Energy, Elsevier, vol. 314(C).
  • Handle: RePEc:eee:energy:v:314:y:2025:i:c:s0360544224040684
    DOI: 10.1016/j.energy.2024.134290
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    1. Genave, Anna & Blancard, Stéphane & Garabedian, Sabine, 2020. "An assessment of energy vulnerability in Small Island Developing States," Ecological Economics, Elsevier, vol. 171(C).
    2. Li, Juan & Ma, Shaoqi & Qu, Yi & Wang, Jiamin, 2023. "The impact of artificial intelligence on firms’ energy and resource efficiency: Empirical evidence from China," Resources Policy, Elsevier, vol. 82(C).
    3. Gordon Cordina, 2004. "Economic Vulnerability And Economic Growth: Some Results From A Neo-Classical Growth Modelling Approach," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 29(2), pages 21-39, December.
    4. Ha, Le Thanh, 2022. "Storm after the Gloomy days: Influences of COVID-19 pandemic on volatility of the energy market," Resources Policy, Elsevier, vol. 79(C).
    5. Liu, Yang & Dong, Kangyin & Jiang, Qingzhe, 2023. "Assessing energy vulnerability and its impact on carbon emissions: A global case," Energy Economics, Elsevier, vol. 119(C).
    6. Yang, Senmiao & Wang, Jianda & Dong, Kangyin & Dong, Xiucheng & Wang, Kun & Fu, Xiaowen, 2024. "Is artificial intelligence technology innovation a recipe for low-carbon energy transition? A global perspective," Energy, Elsevier, vol. 300(C).
    7. Pan, Yuling & Dong, Feng, 2023. "The impacts of energy finance policies and renewable energy subsidy on energy vulnerability under carbon peaking scenarios," Energy, Elsevier, vol. 273(C).
    8. Wang, Bo & Wang, Jianda & Dong, Kangyin & Nepal, Rabindra, 2024. "How does artificial intelligence affect high-quality energy development? Achieving a clean energy transition society," Energy Policy, Elsevier, vol. 186(C).
    9. Gnansounou, Edgard, 2008. "Assessing the energy vulnerability: Case of industrialised countries," Energy Policy, Elsevier, vol. 36(10), pages 3734-3744, October.
    10. Zhao, Congyu & Dong, Kangyin & Wang, Kun & Nepal, Rabindra, 2024. "How does artificial intelligence promote renewable energy development? The role of climate finance," Energy Economics, Elsevier, vol. 133(C).
    11. Lee, Chien-Chiang & Yan, Jingyang, 2024. "Will artificial intelligence make energy cleaner? Evidence of nonlinearity," Applied Energy, Elsevier, vol. 363(C).
    12. Bardazzi, Rossella & Charlier, Dorothée & Legendre, Berangère & Pazienza, Maria Grazia, 2023. "Energy vulnerability in Mediterranean countries: A latent class analysis approach," Energy Economics, Elsevier, vol. 126(C).
    13. Song, Yuegang & Wang, Ziqi & Song, Changqing & Wang, Jianhua & Liu, Rong, 2024. "Impact of artificial intelligence on renewable energy supply chain vulnerability: Evidence from 61 countries," Energy Economics, Elsevier, vol. 131(C).
    14. Anna Genave, 2019. "Energy vulnerability in the Southwest Indian Ocean islands," Post-Print hal-03544904, HAL.
    Full references (including those not matched with items on IDEAS)

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