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Assessing the impact of artificial intelligence on the transition to renewable energy? Analysis of U.S. states under policy uncertainty

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  • Fang, Yuzhu
  • Lee, Chi-Chuan
  • Li, Xinghao

Abstract

In the context of the increasingly severe global climate change, technological innovation and energy transition have formed a critical path to achieving sustainable development. This research employs panel data from 51 states/district in the United States for 2018–2021 to explore the impact of artificial intelligence (AI) development on energy transition and discusses the moderating effect of economic policy uncertainty. The results indicate that AI has a significantly positive impact on energy transition. Economic policy uncertainty at the state level has a significantly positive moderating effect on AI's impact on energy transition, but national-level policy uncertainty does not affect their nexus. AI has a significantly positive correlation with energy transition in states with high electricity prices, low electricity consumption, and those states that are net electricity consumers, while its impact is also significant in regions with frequent extreme weather events. Heterogeneity analysis based on different geographical locations and economic characteristics shows that AI significantly promotes energy transition in the West and Midwest regions. Furthermore, AI significantly promotes the consumption of wind, solar, and hydropower, but inhibits biomass consumption. From the above results, this paper offers relevant policy recommendations.

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  • 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).
    • Handle: RePEc:eee:renene:v:246:y:2025:i:c:s0960148125006317
    DOI: 10.1016/j.renene.2025.122969
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    1. Sun, Huaping & Edziah, Bless Kofi & Kporsu, Anthony Kwaku & Sarkodie, Samuel Asumadu & Taghizadeh-Hesary, Farhad, 2021. "Energy efficiency: The role of technological innovation and knowledge spillover," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    2. Chang, Lei & Taghizadeh-Hesary, Farhad & Mohsin, Muhammad, 2023. "Role of artificial intelligence on green economic development: Joint determinates of natural resources and green total factor productivity," Resources Policy, Elsevier, vol. 82(C).
    3. Daron Acemoglu & Pascual Restrepo, 2018. "Low-Skill and High-Skill Automation," Journal of Human Capital, University of Chicago Press, vol. 12(2), pages 204-232.
    4. Daron Acemoglu & Pascual Restrepo, 2018. "The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment," American Economic Review, American Economic Association, vol. 108(6), pages 1488-1542, June.
    5. David Hémous & Morten Olsen, 2022. "The Rise of the Machines: Automation, Horizontal Innovation, and Income Inequality," American Economic Journal: Macroeconomics, American Economic Association, vol. 14(1), pages 179-223, January.
    6. Carissa Wong, 2024. "How AI is improving climate forecasts," Nature, Nature, vol. 628(8009), pages 710-712, April.
    7. 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).
    8. Kristina McElheran & J. Frank Li & Erik Brynjolfsson & Zachary Kroff & Emin Dinlersoz & Lucia Foster & Nikolas Zolas, 2024. "AI adoption in America: Who, what, and where," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 33(2), pages 375-415, March.
    9. He, Xiaoping & Xu, Cheng, 2024. "Is policy uncertainty always harmful? - Empirical evidence from China's energy policy and city green transition," Energy, Elsevier, vol. 291(C).
    10. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    11. Mir Sayed Shah Danish & Tomonobu Senjyu, 2023. "AI-Enabled Energy Policy for a Sustainable Future," Sustainability, MDPI, vol. 15(9), pages 1-16, May.
    12. Lee, Chi-Chuan & Song, Hepeng & An, Jiafu, 2024. "The impact of green finance on energy transition: Does climate risk matter?," Energy Economics, Elsevier, vol. 129(C).
    13. Ai, Hongshan & Wu, Xiaofei & Li, Ke, 2020. "Differentiated effects of diversified technological sources on China's electricity consumption: Evidence from the perspective of rebound effect," Energy Policy, Elsevier, vol. 137(C).
    14. Xinge Feng & Weijie Luo & Yong Wang, 2023. "Economic policy uncertainty and firm performance: evidence from China," Journal of the Asia Pacific Economy, Taylor & Francis Journals, vol. 28(4), pages 1476-1493, October.
    15. Morgan R. Frank & David Autor & James E. Bessen & Erik Brynjolfsson & Manuel Cebrian & David J. Deming & Maryann Feldman & Matthew Groh & José Lobo & Esteban Moro & Dashun Wang & Hyejin Youn & Iyad Ra, 2019. "Toward understanding the impact of artificial intelligence on labor," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 116(14), pages 6531-6539, April.
    16. 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.
    17. Xi, Yue & Huynh, Anh Ngoc Quang & Jiang, Yushi & Hong, Yanran, 2023. "Energy transition concern: Time-varying effect of climate policy uncertainty on renewables consumption," Technological Forecasting and Social Change, Elsevier, vol. 192(C).
    18. Rebecca Newman & Ilan Noy, 2023. "The global costs of extreme weather that are attributable to climate change," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    19. Baker, Scott R. & Davis, Steven J. & Levy, Jeffrey A., 2022. "State-level economic policy uncertainty," Journal of Monetary Economics, Elsevier, vol. 132(C), pages 81-99.
    20. Amar Rao & Marco Tedeschi & Kamel Si Mohammed & Umer Shahzad, 2024. "Role of Economic Policy Uncertainty in Energy Commodities Prices Forecasting: Evidence from a Hybrid Deep Learning Approach," Computational Economics, Springer;Society for Computational Economics, vol. 64(6), pages 3295-3315, December.
    21. Qiang Wang & Yuanfan Li & Rongrong Li, 2024. "Ecological footprints, carbon emissions, and energy transitions: the impact of artificial intelligence (AI)," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 11(1), pages 1-18, December.
    22. Lee, Chien-Chiang & Yan, Jingyang, 2024. "Will artificial intelligence make energy cleaner? Evidence of nonlinearity," Applied Energy, Elsevier, vol. 363(C).
    23. Marius-Corneliu Marinaș & Marin Dinu & Aura-Gabriela Socol & Cristian Socol, 2018. "Renewable energy consumption and economic growth. Causality relationship in Central and Eastern European countries," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-29, October.
    24. Saura, Jose Ramon & Ribeiro-Navarrete, Samuel & Palacios-Marqués, Daniel & Mardani, Abbas, 2023. "Impact of extreme weather in production economics: Extracting evidence from user-generated content," International Journal of Production Economics, Elsevier, vol. 260(C).
    25. Bogdanov, Dmitrii & Ram, Manish & Aghahosseini, Arman & Gulagi, Ashish & Oyewo, Ayobami Solomon & Child, Michael & Caldera, Upeksha & Sadovskaia, Kristina & Farfan, Javier & De Souza Noel Simas Barbos, 2021. "Low-cost renewable electricity as the key driver of the global energy transition towards sustainability," Energy, Elsevier, vol. 227(C).
    26. Chen, Huangxin & Shi, Yi & Zhao, Xin, 2022. "Investment in renewable energy resources, sustainable financial inclusion and energy efficiency: A case of US economy," Resources Policy, Elsevier, vol. 77(C).
    27. Daron Acemoglu & David Autor & Jonathon Hazell & Pascual Restrepo, 2022. "Artificial Intelligence and Jobs: Evidence from Online Vacancies," Journal of Labor Economics, University of Chicago Press, vol. 40(S1), pages 293-340.
    28. W. M. Nkounga & M. F. Ndiaye & M. L. Ndiaye, 2022. "Management of Intermittent Solar and Wind Energy Resources: Storage and Grid Stabilization," Springer Books, in: Aminata Fall & Reinhard Haas (ed.), Sustainable Energy Access for Communities, chapter 0, pages 109-118, Springer.
    29. Izadyar, Nima & Ong, Hwai Chyuan & Chong, W.T. & Leong, K.Y., 2016. "Resource assessment of the renewable energy potential for a remote area: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 908-923.
    30. Zhang, Yaojie & He, Mengxi & Wang, Yudong & Liang, Chao, 2023. "Global economic policy uncertainty aligned: An informative predictor for crude oil market volatility," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1318-1332.
    31. Xiangyi Li & Qing Wang & Ying Tang, 2024. "The Impact of Artificial Intelligence Development on Urban Energy Efficiency—Based on the Perspective of Smart City Policy," Sustainability, MDPI, vol. 16(8), pages 1-22, April.
    32. 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).
    33. Mariani, Marcello M. & Machado, Isa & Nambisan, Satish, 2023. "Types of innovation and artificial intelligence: A systematic quantitative literature review and research agenda," Journal of Business Research, Elsevier, vol. 155(PB).
    34. Naiara Uriarte-Gallastegi & Germán Arana-Landín & Beñat Landeta-Manzano & Iker Laskurain-Iturbe, 2024. "The Role of AI in Improving Environmental Sustainability: A Focus on Energy Management," Energies, MDPI, vol. 17(3), pages 1-15, January.
    35. Huang, Geng & He, Ling-Yun & Lin, Xi, 2022. "Robot adoption and energy performance: Evidence from Chinese industrial firms," Energy Economics, Elsevier, vol. 107(C).
    36. Hongwen Jia & Shugang Fan & Miao Xia, 2023. "The Impact of Renewable Energy Consumption on Economic Growth: Evidence from Countries along the Belt and Road," Sustainability, MDPI, vol. 15(11), pages 1-11, May.
    37. Lee, Chi-Chuan & Li, Mingyue & Li, Xinghao & Song, Hepeng, 2025. "More green digital finance with less energy poverty? The key role of climate risk," Energy Economics, Elsevier, vol. 141(C).
    38. 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).
    39. 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.
    40. Lee, Chi-Chuan & Fang, Yuzhu, 2025. "Climate finance for energy security: An empirical analysis from a global perspective," Economic Analysis and Policy, Elsevier, vol. 85(C), pages 963-978.
    41. Lyu, Wenjing & Liu, Jin, 2021. "Artificial Intelligence and emerging digital technologies in the energy sector," Applied Energy, Elsevier, vol. 303(C).
    42. Halhoul Merabet, Ghezlane & Essaaidi, Mohamed & Ben Haddou, Mohamed & Qolomany, Basheer & Qadir, Junaid & Anan, Muhammad & Al-Fuqaha, Ala & Abid, Mohamed Riduan & Benhaddou, Driss, 2021. "Intelligent building control systems for thermal comfort and energy-efficiency: A systematic review of artificial intelligence-assisted techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    43. Jun Liu & Yu Qian & Yuanjun Yang & Zhidan Yang, 2022. "Can Artificial Intelligence Improve the Energy Efficiency of Manufacturing Companies? Evidence from China," IJERPH, MDPI, vol. 19(4), pages 1-18, February.
    44. Liu, Liang & Yang, Kun & Fujii, Hidemichi & Liu, Jun, 2021. "Artificial intelligence and energy intensity in China’s industrial sector: Effect and transmission channel," Economic Analysis and Policy, Elsevier, vol. 70(C), pages 276-293.
    45. Yang, Xiaolei & He, Lingyun & Xia, Yufei & Chen, Yufeng, 2019. "Effect of government subsidies on renewable energy investments: The threshold effect," Energy Policy, Elsevier, vol. 132(C), pages 156-166.
    46. Parrish Bergquist & Christopher Warshaw, 2023. "How climate policy commitments influence energy systems and the economies of US states," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
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    2. Laura Vasilescu & Mirela Sichigea & Cătălina Sitnikov & Laurențiu-Stelian Mihai, 2025. "Nexus Between Artificial Intelligence, Renewable Energy, and Economic Development: A Multi-Method Approach," Economies, MDPI, vol. 13(9), pages 1-36, September.

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