IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v149y2025ics0140988325005560.html

Transitioning the energy landscape: AI's role in shifting from fossil fuels to renewable energy

Author

Listed:
  • Li, Zhengzheng
  • Xing, Youze
  • Shao, Xuefeng
  • Zhong, Yifan
  • Su, Yun Hsuan

Abstract

This study examines the evolution of the energy market within the scope of artificial intelligence (AI). By employing wavelet analysis, we discern that AI has predominantly fostered the growth of renewable energy sectors, notably wind and solar energy, across short-, medium- and long-term horizons, except during 2016–2017. This deviation is mainly attributable to supply-side structural reforms. The positive correlation between AI and renewable energy has become increasingly pronounced after 2019, driven by the heightened demand for technological innovation and energy transformation after the pandemic. Conversely, the relationship between AI and fossil fuels fluctuates, exhibiting positive and negative correlations at various stages of AI's development. Our findings, therefore, offer valuable insights for policymakers seeking to design energy transition policies that leverage AI technology.

Suggested Citation

  • Li, Zhengzheng & Xing, Youze & Shao, Xuefeng & Zhong, Yifan & Su, Yun Hsuan, 2025. "Transitioning the energy landscape: AI's role in shifting from fossil fuels to renewable energy," Energy Economics, Elsevier, vol. 149(C).
    • Handle: RePEc:eee:eneeco:v:149:y:2025:i:c:s0140988325005560
    DOI: 10.1016/j.eneco.2025.108729
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988325005560
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2025.108729?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Tascikaraoglu, A. & Uzunoglu, M., 2014. "A review of combined approaches for prediction of short-term wind speed and power," Renewable and Sustainable Energy Reviews, Elsevier, vol. 34(C), pages 243-254.
    2. Zhengzheng Li & Zhongyang Sun & Kaihua Wang & Oana-Ramona Lobonț, 2024. "Symphony or Solo: Does Convergence Exist in Environmental Taxation among EU Countries?," Sustainability, MDPI, vol. 16(17), pages 1-21, September.
    3. Fontoura, Leonardo & Luiz de Mattos Nascimento, Daniel & Neto, Julio Vieira & Gusmão Caiado, Rodrigo Goyannes, 2025. "Energy Gen-AI technology framework: A perspective of energy efficiency and business ethics in operation management," Technology in Society, Elsevier, vol. 81(C).
    4. Su, Chi Wei & Song, Xin Yue & Dou, Junyi & Qin, Meng, 2025. "Fossil fuels or renewable energy? The dilemma of climate policy choices," Renewable Energy, Elsevier, vol. 238(C).
    5. Rusul Abduljabbar & Hussein Dia & Sohani Liyanage & Saeed Asadi Bagloee, 2019. "Applications of Artificial Intelligence in Transport: An Overview," Sustainability, MDPI, vol. 11(1), pages 1-24, January.
    6. Wang, Jianda & Wang, Bo & Dong, Kangyin & Dong, Xiucheng, 2022. "How does the digital economy improve high-quality energy development? The case of China," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    7. Yekini Suberu, Mohammed & Wazir Mustafa, Mohd & Bashir, Nouruddeen, 2014. "Energy storage systems for renewable energy power sector integration and mitigation of intermittency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 499-514.
    8. Li, Hongyu & Lu, Zhiqiang & Zhang, Zhengping & Tanasescu, Cristina, 2025. "How does artificial intelligence affect manufacturing firms' energy intensity?," Energy Economics, Elsevier, vol. 141(C).
    9. Li, Lingxiao & Wen, Jun & Li, Yan & Mu, Zi, 2025. "Supply chain challenges and energy insecurity: The role of AI in facilitating renewable energy transition," Energy Economics, Elsevier, vol. 144(C).
    10. Yang, Shengyao & Zhu, Meng Nan & Yu, Haiyan, 2024. "Are artificial intelligence and blockchain the key to unlocking the box of clean energy?," Energy Economics, Elsevier, vol. 134(C).
    11. Liu, Jun & Chang, Huihong & Forrest, Jeffrey Yi-Lin & Yang, Baohua, 2020. "Influence of artificial intelligence on technological innovation: Evidence from the panel data of china's manufacturing sectors," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    12. Qin, Meng & Hu, Wei & Qi, Xinzhou & Chang, Tsangyao, 2024. "Do the benefits outweigh the disadvantages? Exploring the role of artificial intelligence in renewable energy," Energy Economics, Elsevier, vol. 131(C).
    13. Wang, En-Ze & Lee, Chien-Chiang & Li, Yaya, 2022. "Assessing the impact of industrial robots on manufacturing energy intensity in 38 countries," Energy Economics, Elsevier, vol. 105(C).
    14. Zheng-Zheng Li & Chi-Wei Su & Meng Nan Zhu, 2022. "How Does Uncertainty Affect Volatility Correlation between Financial Assets? Evidence from Bitcoin, Stock and Gold," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 58(9), pages 2682-2694, July.
    15. Nepal, Rabindra & Zhao, Xiaomeng & Dong, Kangyin & Wang, Jianda & Sharif, Arshian, 2025. "Can artificial intelligence technology innovation boost energy resilience? The role of green finance," Energy Economics, Elsevier, vol. 142(C).
    16. Qin, Meng & Wan, Yue & Dou, Junyi & Su, Chi Wei, 2024. "Artificial Intelligence: Intensifying or mitigating unemployment?," Technology in Society, Elsevier, vol. 79(C).
    17. Luís Aguiar-Conraria & Maria Joana Soares, 2014. "The Continuous Wavelet Transform: Moving Beyond Uni- And Bivariate Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 28(2), pages 344-375, April.
    18. Ricardo Vinuesa & Hossein Azizpour & Iolanda Leite & Madeline Balaam & Virginia Dignum & Sami Domisch & Anna Felländer & Simone Daniela Langhans & Max Tegmark & Francesco Fuso Nerini, 2020. "The role of artificial intelligence in achieving the Sustainable Development Goals," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    19. Uzlu, Ergun & Akpınar, Adem & Özturk, Hasan Tahsin & Nacar, Sinan & Kankal, Murat, 2014. "Estimates of hydroelectric generation using neural networks with the artificial bee colony algorithm for Turkey," Energy, Elsevier, vol. 69(C), pages 638-647.
    20. Philip J. Heptonstall & Robert J. K. Gross, 2021. "A systematic review of the costs and impacts of integrating variable renewables into power grids," Nature Energy, Nature, vol. 6(1), pages 72-83, January.
    21. 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).
    22. Todd Levin & John Bistline & Ramteen Sioshansi & Wesley J. Cole & Jonghwan Kwon & Scott P. Burger & George W. Crabtree & Jesse D. Jenkins & Rebecca O’Neil & Magnus Korpås & Sonja Wogrin & Benjamin F. , 2023. "Energy storage solutions to decarbonize electricity through enhanced capacity expansion modelling," Nature Energy, Nature, vol. 8(11), pages 1199-1208, November.
    23. Lee, Chi-Chuan & Fang, Yuzhu & Quan, Shiyun & Li, Xinghao, 2024. "Leveraging the power of artificial intelligence toward the energy transition: The key role of the digital economy," Energy Economics, Elsevier, vol. 135(C).
    24. Qi, Shaozhou & Pang, Lidong & Qi, Tianbai & Zhang, Xiaoling & Pirtea, Marilen Gabriel, 2024. "The correlation between the green bond market and carbon trading markets under climate change: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    25. Sivasubramanian Manikandan & Rangarajan Sindhu Kaviya & Dhamodharan Hemnath Shreeharan & Ramasamy Subbaiya & Sundaram Vickram & Natchimuthu Karmegam & Woong Kim & Muthusamy Govarthanan, 2025. "Artificial intelligence‐driven sustainability: Enhancing carbon capture for sustainable development goals– A review," Sustainable Development, John Wiley & Sons, Ltd., vol. 33(2), pages 2004-2029, April.
    26. Lee, Chien-Chiang & Yan, Jingyang, 2024. "Will artificial intelligence make energy cleaner? Evidence of nonlinearity," Applied Energy, Elsevier, vol. 363(C).
    27. Baseer, Mohammad Abdul & Kumar, Prashant & Nascimento, Erick Giovani Sperandio, 2025. "Advancements in hydrogen production through the integration of renewable energy sources with AI techniques: A comprehensive literature review," Applied Energy, Elsevier, vol. 383(C).
    28. 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).
    29. Qi, Shaozhou & Pang, Lidong & Li, Xinqiang & Huang, Lin, 2025. "The dynamic connectedness in the “carbon-energy-green finance” system: The role of climate policy uncertainty and artificial intelligence," Energy Economics, Elsevier, vol. 143(C).
    30. Huang, Meiying & Li, Quan & Li, Bowen, 2025. "From algorithms to green growth: Can artificial intelligence drive enterprise energy transformation?," Economic Analysis and Policy, Elsevier, vol. 85(C), pages 1846-1866.
    31. Zhang, Xiaojing & Khan, Khalid & Shao, Xuefeng & Oprean-Stan, Camelia & Zhang, Qian, 2024. "The rising role of artificial intelligence in renewable energy development in China," Energy Economics, Elsevier, vol. 132(C).
    32. Yousaf, Imran & Ijaz, Muhammad Shahzad & Umar, Muhammad & Li, Yanshuang, 2024. "Exploring volatility interconnections between AI tokens, AI stocks, and fossil fuel markets: evidence from time and frequency-based connectedness analysis," Energy Economics, Elsevier, vol. 133(C).
    33. Zhou, Wei & Zhuang, Yan & Chen, Yan, 2024. "How does artificial intelligence affect pollutant emissions by improving energy efficiency and developing green technology," Energy Economics, Elsevier, vol. 131(C).
    34. Saxena, Vivek & Kumar, Narendra & Manna, Saibal & Rajput, Saurabh Kumar & Agarwal, Kusum Lata & Diwania, Sourav & Gupta, Varun, 2025. "Modelling, solution and application of optimization techniques in HRES: From conventional to artificial intelligence," Applied Energy, Elsevier, vol. 380(C).
    35. Dan Tong & David J. Farnham & Lei Duan & Qiang Zhang & Nathan S. Lewis & Ken Caldeira & Steven J. Davis, 2021. "Geophysical constraints on the reliability of solar and wind power worldwide," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    36. Zhao, Qian & Wang, Lu & Stan, Sebastian-Emanuel & Mirza, Nawazish, 2024. "Can artificial intelligence help accelerate the transition to renewable energy?," Energy Economics, Elsevier, vol. 134(C).
    37. Bernd W. Wirtz & Jan C. Weyerer & Carolin Geyer, 2019. "Artificial Intelligence and the Public Sector—Applications and Challenges," International Journal of Public Administration, Taylor & Francis Journals, vol. 42(7), pages 596-615, May.
    38. Yijing Wang & Rong Wang & Katsumasa Tanaka & Philippe Ciais & Josep Penuelas & Yves Balkanski & Jordi Sardans & Didier Hauglustaine & Wang Liu & Xiaofan Xing & Jiarong Li & Siqing Xu & Yuankang Xiong , 2023. "Accelerating the energy transition towards photovoltaic and wind in China," Nature, Nature, vol. 619(7971), pages 761-767, July.
    39. Wen, Jun & Yin, Hua-Tang & Chang, Chun-Ping & Tang, Kai, 2024. "How AI shapes greener futures: Comparative insights from equity vs debt investment responses in renewable energy," Energy Economics, Elsevier, vol. 136(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Li, Zhengzheng & Liu, Shenyu & Lobont, Oana-Ramona, 2026. "Oil price uncertainty and China's rare earth exports: Driver or constraint?," Energy Policy, Elsevier, vol. 208(C).
    2. Wang, Yanyan & Chu, Fuling, 2025. "How does artificial intelligence impact household energy poverty? Empirical evidence from China," Energy, Elsevier, vol. 341(C).
    3. Gupta, Aparna & Osipov, Denis, 2025. "Performance risk scoring of risk-free renewable generation bids," Energy, Elsevier, vol. 338(C).
    4. Zi-Han Liu & Zheng-Zheng Li & Oana Ramona Lobonț & Kai-Hua Wang, 2025. "How Does Fintech Affect Green Total Factor Energy Efficiency? Evidence from 240 Cities in China," Sustainability, MDPI, vol. 17(19), pages 1-25, September.
    5. Naveed Khan & Anam Tariq & Syed Zulfiqar Ali Shah & Hassan Javed, 2026. "Quantile time–frequency connectedness and spillover between artificial intelligence, clean energy, and traditional asset classes: insights and portfolio implications," Future Business Journal, Springer, vol. 12(1), pages 1-39, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dong, Zequn & Tan, Chaodan & Ma, Biao & Ning, Zhaoshuo, 2024. "The impact of artificial intelligence on the energy transition: The role of regulatory quality as a guardrail, not a wall," Energy Economics, Elsevier, vol. 140(C).
    2. Wang, Qiang & Zhang, Siqi & Li, Rongrong, 2026. "Artificial intelligence in the renewable energy transition: The critical role of financial development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 226(PA).
    3. Zhang, Wei & Zhang, Yunjia & Lan, Xuling & Song, Malin, 2025. "“Green BRICS”: How artificial intelligence can build the explicit structure and implicit order of energy transition," Energy Economics, Elsevier, vol. 149(C).
    4. Gao, Xiangming & Ji, Xinliang & Wang, Rong & Yu, Jian, 2025. "The effect of artificial intelligence on energy transition: Evidence from China," Energy Economics, Elsevier, vol. 147(C).
    5. Li, Wen & Li, Jing-Ping & Wang, Yun-Feng & Stan, Sebastian-Emanuel, 2025. "Is artificial intelligence an impediment or an impetus to renewable energy investment? Evidence from China," Energy Economics, Elsevier, vol. 147(C).
    6. Zhu, Qingyuan & Sun, Chenhao & Xu, Chengzhen & Geng, Qianqian, 2025. "The impact of artificial intelligence on global energy vulnerability," Economic Analysis and Policy, Elsevier, vol. 85(C), pages 15-27.
    7. Li, Lingxiao & Wen, Jun & Li, Yan & Mu, Zi, 2025. "Supply chain challenges and energy insecurity: The role of AI in facilitating renewable energy transition," Energy Economics, Elsevier, vol. 144(C).
    8. Zhang, Wenwen & Fu, Shuai & Chiu, Yi-Bin & Hsiao, Cody Yu-Ling, 2025. "Artificial intelligence, digital inclusive finance, and financial performance: Dynamic threshold insights from renewable energy enterprises," Energy Economics, Elsevier, vol. 148(C).
    9. Niu, Xiaotong & Lin, Changao & He, Shanshan & Yang, Youcai, 2025. "Artificial intelligence and enterprise pollution emissions: From the perspective of energy transition," Energy Economics, Elsevier, vol. 144(C).
    10. Shao, Mingxing & Wen, Lei & Li, Sifei & Huang, Binyue, 2025. "Exploring the role of artificial intelligence as a catalyst for energy technology innovation," Energy Economics, Elsevier, vol. 147(C).
    11. Zheng, Huanyu & Wu, Jie & Li, Runze & Song, Yanwu, 2025. "The role of artificial intelligence in renewable energy development: Insights from less developed economies," Energy Economics, Elsevier, vol. 146(C).
    12. Lee, Chien-Chiang & Zou, Jinyang & Chen, Pei-Fen, 2025. "The impact of artificial intelligence on the energy consumption of corporations: The role of human capital," Energy Economics, Elsevier, vol. 143(C).
    13. Chen, Zhan-Ming & Xiong, Qiyang & Duan, Jiahui & Ma, Jianhong & Chen, Zhuo & Guo, Shan, 2025. "AI carbon footprint in China sets to double post-2030 carbon peaking," Energy Economics, Elsevier, vol. 150(C).
    14. Gao, Lan & Wang, Jing, 2025. "Can artificial intelligence reduce energy vulnerability? Evidence from an international perspective," Energy Economics, Elsevier, vol. 145(C).
    15. Zhilun Jiao & Chenrui Zhang & Wenwen Li, 2025. "Artificial Intelligence in Energy Economics Research: A Bibliometric Review," Energies, MDPI, vol. 18(2), pages 1-30, January.
    16. Li, Cong & Zhang, Yue & Liu, Xihua & Sun, Jiawen, 2025. "Does artificial intelligence promote green technology innovation in the energy industry?," Energy Economics, Elsevier, vol. 144(C).
    17. Fang, Yuzhu & Lee, Chi-Chuan & Li, Xinghao, 2025. "Assessing the impact of artificial intelligence on the transition to renewable energy? Analysis of U.S. states under policy uncertainty," Renewable Energy, Elsevier, vol. 246(C).
    18. Zhong, Chao & Cai, Hongbo & Fang, Shuai & Xue, Rui & Shan, Yuli, 2025. "Does artificial intelligence reduce energy intensity in manufacturing? Evidence from country-level data," Energy Economics, Elsevier, vol. 149(C).
    19. Naveed Khan & Anam Tariq & Syed Zulfiqar Ali Shah & Hassan Javed, 2026. "Quantile time–frequency connectedness and spillover between artificial intelligence, clean energy, and traditional asset classes: insights and portfolio implications," Future Business Journal, Springer, vol. 12(1), pages 1-39, December.
    20. Huang, Yujie & Liu, Shucheng & Gan, Jiawu & Liu, Baoliu & Wu, Yuxi, 2024. "How does the construction of new generation of national AI innovative development pilot zones drive enterprise ESG development? Empirical evidence from China," Energy Economics, Elsevier, vol. 140(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:149:y:2025:i:c:s0140988325005560. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.