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The effect of artificial intelligence on energy transition: Evidence from China

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  • Gao, Xiangming
  • Ji, Xinliang
  • Wang, Rong
  • Yu, Jian

Abstract

Artificial intelligence (AI) is an important next-generation information technology and a key driver of energy transition. Using panel data from 282 cities from 2006 to 2019, in this study, we examine the influence of AI on energy transition in China. We measure AI using exposure to industrial robots and find that AI can significantly accelerate the energy transition process. Improvements in energy efficiency and research and development innovation are the two mechanisms through which AI promotes energy transition. The results of heterogeneity analysis indicate that AI's impact on energy transition is more pronounced in cities with a high transition potential, specifically those with a low level of electrification, weak environmental regulations, greater fiscal constraints, and those located in the central and western regions of China. These findings provide valuable insights for the application of AI in the field of energy transition and policy guidance for China and other developing countries.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:eneeco:v:147:y:2025:i:c:s0140988325003925
    DOI: 10.1016/j.eneco.2025.108568
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    1. 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.
    2. Rodríguez, Fermín & Fleetwood, Alice & Galarza, Ainhoa & Fontán, Luis, 2018. "Predicting solar energy generation through artificial neural networks using weather forecasts for microgrid control," Renewable Energy, Elsevier, vol. 126(C), pages 855-864.
    3. Lin, Boqiang & Omoju, Oluwasola E., 2017. "Focusing on the right targets: Economic factors driving non-hydro renewable energy transition," Renewable Energy, Elsevier, vol. 113(C), pages 52-63.
    4. Xu, Runguo & Chen, Xi & Dong, Peng, 2024. "Nexus among financial technologies, oil rents, governance and energy transition: Panel investigation from Asian Economies," Resources Policy, Elsevier, vol. 90(C).
    5. Hossain, Mohammad Razib & Rao, Amar & Sharma, Gagan Deep & Dev, Dhairya & Kharbanda, Aeshna, 2024. "Empowering energy transition: Green innovation, digital finance, and the path to sustainable prosperity through green finance initiatives," Energy Economics, Elsevier, vol. 136(C).
    6. Child, Michael & Breyer, Christian, 2017. "Transition and transformation: A review of the concept of change in the progress towards future sustainable energy systems," Energy Policy, Elsevier, vol. 107(C), pages 11-26.
    7. Hanif, Imran & Aziz, Babar & Chaudhry, Imran Sharif, 2019. "Carbon emissions across the spectrum of renewable and nonrenewable energy use in developing economies of Asia," Renewable Energy, Elsevier, vol. 143(C), pages 586-595.
    8. Wang, Xueyang & Sun, Xiumei & Ahmad, Mahmood & Chen, Jiawei, 2024. "Energy transition, ecological governance, globalization, and environmental sustainability: Insights from the top ten emitting countries," Energy, Elsevier, vol. 292(C).
    9. Asadi Aghajari, H. & Niknam, T. & Shasadeghi, M. & Sharifhosseini, S.M. & Taabodi, M.H. & Sheybani, Ehsan & Javidi, Giti & Pourbehzadi, Motahareh, 2025. "Analyzing complexities of integrating Renewable Energy Sources into Smart Grid: A comprehensive review," Applied Energy, Elsevier, vol. 383(C).
    10. Ajay Agrawal & Joshua Gans & Avi Goldfarb, 2018. "Prediction, Judgment, and Complexity: A Theory of Decision-Making and Artificial Intelligence," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 89-110, National Bureau of Economic Research, Inc.
    11. Ding, Tao & Li, Hao & Liu, Li & Feng, Kui, 2024. "An inquiry into the nexus between artificial intelligence and energy poverty in the light of global evidence," Energy Economics, Elsevier, vol. 136(C).
    12. Jing Gao & Lei Zhang, 2021. "Does biomass energy consumption mitigate CO2 emissions? The role of economic growth and urbanization: evidence from developing Asia," Journal of the Asia Pacific Economy, Taylor & Francis Journals, vol. 26(1), pages 96-115, January.
    13. Neofytou, H. & Nikas, A. & Doukas, H., 2020. "Sustainable energy transition readiness: A multicriteria assessment index," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    14. Daron Acemoglu & Pascual Restrepo, 2020. "The wrong kind of AI? Artificial intelligence and the future of labour demand," Cambridge Journal of Regions, Economy and Society, Cambridge Political Economy Society, vol. 13(1), pages 25-35.
    15. Jung, Jin Hwa & Lim, Dong-Geon, 2020. "Industrial robots, employment growth, and labor cost: A simultaneous equation analysis," Technological Forecasting and Social Change, Elsevier, vol. 159(C).
    16. Yang, Chih-Hai, 2022. "How Artificial Intelligence Technology Affects Productivity and Employment: Firm-level Evidence from Taiwan," Research Policy, Elsevier, vol. 51(6).
    17. Chi Wei Su & Shuqi Lv & Meng Qin & Diego Norena-Chavez, 2024. "Uncertainty and Credit: The Chicken or the Egg Causality Dilemma," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 60(11), pages 2560-2578, September.
    18. Shi, Zhongtuo & Yao, Wei & Li, Zhouping & Zeng, Lingkang & Zhao, Yifan & Zhang, Runfeng & Tang, Yong & Wen, Jinyu, 2020. "Artificial intelligence techniques for stability analysis and control in smart grids: Methodologies, applications, challenges and future directions," Applied Energy, Elsevier, vol. 278(C).
    19. Li, Yaya & Zhang, Yuru & Pan, An & Han, Minchun & Veglianti, Eleonora, 2022. "Carbon emission reduction effects of industrial robot applications: Heterogeneity characteristics and influencing mechanisms," Technology in Society, Elsevier, vol. 70(C).
    20. Wang, Qunwei & Zhou, Bo & Zhang, Cheng & Zhou, Dequn, 2021. "Do energy subsidies reduce fiscal and household non-energy expenditures? A regional heterogeneity assessment on coal-to-gas program in China," Energy Policy, Elsevier, vol. 155(C).
    21. Zhong, Kai & Song, Liangrong, 2025. "Artificial intelligence adoption and corporate green innovation capability," Finance Research Letters, Elsevier, vol. 72(C).
    22. 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).
    23. 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).
    24. Aslam, Naveed & Yang, Wanping & Saeed, Rabia & Ullah, Fahim, 2024. "Energy transition as a solution for energy security risk: Empirical evidence from BRI countries," Energy, Elsevier, vol. 290(C).
    25. Sun, Yunpeng & Gao, Pengpeng & Razzaq, Asif, 2023. "How does fiscal decentralization lead to renewable energy transition and a sustainable environment? Evidence from highly decentralized economies," Renewable Energy, Elsevier, vol. 206(C), pages 1064-1074.
    26. Emodi, Nnaemeka Vincent & Haruna, Emmanuel Umoru & Abdu, Nizam & Aldana Morataya, Sergio David & Dioha, Michael O. & Abraham-Dukuma, Magnus C., 2022. "Urban and rural household energy transition in Sub-Saharan Africa: Does spatial heterogeneity reveal the direction of the transition?," Energy Policy, Elsevier, vol. 168(C).
    27. Stephen Taiwo Onifade & Andrew Adewale Alola, 2022. "Energy transition and environmental quality prospects in leading emerging economies: The role of environmental‐related technological innovation," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(6), pages 1766-1778, December.
    28. Jiang, Mingdong & Yu, Xinxin, 2025. "Enhancing the resilience of urban energy systems: The role of artificial intelligence," Energy Economics, Elsevier, vol. 144(C).
    29. Daron Acemoglu & David Hemous & Lint Barrage & Philippe Aghion, 2019. "Climate Change, Directed Innovation, and Energy Transition: The Long-run Consequences of the Shale Gas Revolution," 2019 Meeting Papers 1302, Society for Economic Dynamics.
    30. Chishti, Muhammad Zubair & Xia, Xiqiang & Dogan, Eyup, 2025. "Corrigendum to “Understanding the effects of artificial intelligence on energy transition: The moderating role of Paris Agreement” [Energy Economics Volume 131, March 2024, 107388]," Energy Economics, Elsevier, vol. 142(C).
    31. Marta Ewa Kuc-Czarnecka & Magdalena Olczyk & Marek Zinecker, 2021. "Improvements and Spatial Dependencies in Energy Transition Measures," Energies, MDPI, vol. 14(13), pages 1-22, June.
    32. Parteka, Aleksandra & Kordalska, Aleksandra, 2023. "Artificial intelligence and productivity: global evidence from AI patent and bibliometric data," Technovation, Elsevier, vol. 125(C).
    33. Jagadeesh Kumar, M. & Sampradeepraj, T. & Sivajothi, E. & Singh, Gurkirpal, 2024. "An efficient hybrid technique for energy management system with renewable energy system and energy storage system in smart grid," Energy, Elsevier, vol. 306(C).
    34. Das, Utpal Kumar & Tey, Kok Soon & Seyedmahmoudian, Mehdi & Mekhilef, Saad & Idris, Moh Yamani Idna & Van Deventer, Willem & Horan, Bend & Stojcevski, Alex, 2018. "Forecasting of photovoltaic power generation and model optimization: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 912-928.
    35. 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).
    36. Lin, Boqiang & Omoju, Oluwasola E. & Okonkwo, Jennifer U., 2016. "Factors influencing renewable electricity consumption in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 687-696.
    37. Gozgor, Giray & Paramati, Sudharshan Reddy, 2022. "Does energy diversification cause an economic slowdown? Evidence from a newly constructed energy diversification index," Energy Economics, Elsevier, vol. 109(C).
    38. Li, Hongyu & Lu, Zhiqiang & Zhang, Zhengping & Tanasescu, Cristina, 2025. "How does artificial intelligence affect manufacturing firms' energy intensity?," Energy Economics, Elsevier, vol. 141(C).
    39. Wang, Zongrun & Zhang, Taiyu & Ren, Xiaohang & Shi, Yukun, 2024. "AI adoption rate and corporate green innovation efficiency: Evidence from Chinese energy companies," Energy Economics, Elsevier, vol. 132(C).
    40. Lau, Chi Keung & Gozgor, Giray & Mahalik, Mantu Kumar & Patel, Gupteswar & Li, Jing, 2023. "Introducing a new measure of energy transition: Green quality of energy mix and its impact on CO2 emissions," Energy Economics, Elsevier, vol. 122(C).
    41. Boza, Pal & Evgeniou, Theodoros, 2021. "Artificial intelligence to support the integration of variable renewable energy sources to the power system," Applied Energy, Elsevier, vol. 290(C).
    42. Zhong, Wenli & Liu, Yang & Dong, Kangyin & Ni, Guohua, 2024. "Assessing the synergistic effects of artificial intelligence on pollutant and carbon emission mitigation in China," Energy Economics, Elsevier, vol. 138(C).
    43. Lee, Chien-Chiang & Yan, Jingyang, 2024. "Will artificial intelligence make energy cleaner? Evidence of nonlinearity," Applied Energy, Elsevier, vol. 363(C).
    44. Yaya Li & Yuru Zhang & An Pan & Minchun Han & Eleonora Veglianti, 2022. "Carbon emission reduction effects of industrial robot applications: Heterogeneity characteristics and influencing mechanisms," Post-Print hal-04522085, HAL.
    45. Raza, Muhammad Qamar & Khosravi, Abbas, 2015. "A review on artificial intelligence based load demand forecasting techniques for smart grid and buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 1352-1372.
    46. 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).
    47. Aljoša Slameršak & Giorgos Kallis & Daniel W. O’Neill, 2022. "Energy requirements and carbon emissions for a low-carbon energy transition," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    48. Dong, Kangyin & Jiang, Qingzhe & Shahbaz, Muhammad & Zhao, Jun, 2021. "Does low-carbon energy transition mitigate energy poverty? The case of natural gas for China," Energy Economics, Elsevier, vol. 99(C).
    49. Wang, Jianda & Wang, Kun & Dong, Kangyin & Zhang, Shiqiu, 2023. "Assessing the role of financial development in natural resource utilization efficiency: Does artificial intelligence technology matter?," Resources Policy, Elsevier, vol. 85(PA).
    50. Su, Xiang & Tan, Junlan, 2023. "Regional energy transition path and the role of government support and resource endowment in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 174(C).
    51. Bourcet, Clémence, 2020. "Empirical determinants of renewable energy deployment: A systematic literature review," Energy Economics, Elsevier, vol. 85(C).
    52. Bai, Rui & Lin, Boqiang, 2023. "Nexus between green finance development and green technological innovation: A potential way to achieve the renewable energy transition," Renewable Energy, Elsevier, vol. 218(C).
    53. Che, Xiao-Jing & Zhou, P. & Chai, Kah-Hin, 2022. "Regional policy effect on photovoltaic (PV) technology innovation: Findings from 260 cities in China," Energy Policy, Elsevier, vol. 162(C).
    54. Chi Wei Su & Xiaofeng Liu & Meng Qin & Muhammad Umar, 2024. "Is the Uncertainty Economic Policy an Impediment or an Impetus to Technological Innovation?," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 60(11), pages 2579-2593, September.
    55. Su, Chi-Wei & Yang, Shengyao & Dumitrescu Peculea, Adelina & Ioana Biţoiu, Teodora & Qin, Meng, 2024. "Energy imports in turbulent eras: Evidence from China," Energy, Elsevier, vol. 306(C).
    56. Mugume, Regean & Bulime, Enock W.N., 2024. "Delivering double wins: How can Africa's finance deliver economic growth and renewable energy transition?," Renewable Energy, Elsevier, vol. 224(C).
    57. Moraga, J. & Duzgun, H.S. & Cavur, M. & Soydan, H., 2022. "The Geothermal Artificial Intelligence for geothermal exploration," Renewable Energy, Elsevier, vol. 192(C), pages 134-149.
    58. Liu, Yingji & Shen, Fangbing & Guo, Ju & Hu, Guoheng & Song, Yuegang, 2025. "Can artificial intelligence technology improve companies' capacity for green innovation? Evidence from listed companies in China," Energy Economics, Elsevier, vol. 143(C).
    59. Giudici, Paolo & Raffinetti, Emanuela, 2023. "SAFE Artificial Intelligence in finance," Finance Research Letters, Elsevier, vol. 56(C).
    60. Lee, Chien-Chiang & Qin, Shuai & Li, Yaya, 2022. "Does industrial robot application promote green technology innovation in the manufacturing industry?," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    61. Wang, Zongrun & Cao, Xuxin & Ren, Xiaohang & Gozgor, Giray, 2024. "Digital finance and the energy transition: Evidence from Chinese prefecture-level cities," Global Finance Journal, Elsevier, vol. 61(C).
    62. Yang, Gangqiang & Nie, Yiming & Li, Honggui & Wang, Haisen, 2023. "Digital transformation and low-carbon technology innovation in manufacturing firms: The mediating role of dynamic capabilities," International Journal of Production Economics, Elsevier, vol. 263(C).
    63. Cao, Fangzhi & Su, Chi-Wei & Qin, Meng & Moldovan, Nicoleta-Claudia, 2024. "The investment of renewable energy: Is green bond a safe-haven to hedge U.S. monetary policy uncertainty?," Energy, Elsevier, vol. 307(C).
    64. Gianluca Biggi & Martina Iori & Julia Mazzei & Andrea Mina, 2025. "Green intelligence: the AI content of green technologies," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 15(3), pages 803-840, September.
    65. Fan, Jingjing & Wang, Jianliang & Qiu, Jixiang & Li, Nu, 2023. "Stage effects of energy consumption and carbon emissions in the process of urbanization: Evidence from 30 provinces in China," Energy, Elsevier, vol. 276(C).
    66. Yang, Zhaofu & Liu, Hong & Yuan, Yongna & Li, Muhua, 2024. "Can renewable energy development facilitate China's sustainable energy transition? Perspective from Energy Trilemma," Energy, Elsevier, vol. 304(C).
    67. Yuan, Meng & Thellufsen, Jakob Zinck & Lund, Henrik & Liang, Yongtu, 2021. "The electrification of transportation in energy transition," Energy, Elsevier, vol. 236(C).
    68. Sarsar, Lamiae & Echaoui, Abdellah, 2024. "Empirical analysis of the economic complexity boost on the impact of energy transition on economic growth: A panel data study of 124 countries," Energy, Elsevier, vol. 294(C).
    69. Liu, Yang & Dong, Kangyin & Taghizadeh-Hesary, Farhad & Dong, Xiucheng, 2024. "How do minerals affect the global energy transition? Metallic versus non-metallic mineral," Resources Policy, Elsevier, vol. 92(C).
    70. Huang, Lingyun & Zou, Yanjun, 2020. "How to promote energy transition in China: From the perspectives of interregional relocation and environmental regulation," Energy Economics, Elsevier, vol. 92(C).
    71. Qin, Meng & Wan, Yue & Dou, Junyi & Su, Chi Wei, 2024. "Artificial Intelligence: Intensifying or mitigating unemployment?," Technology in Society, Elsevier, vol. 79(C).
    72. Stefano Baruffaldi & Brigitte van Beuzekom & Hélène Dernis & Dietmar Harhoff & Nandan Rao & David Rosenfeld & Mariagrazia Squicciarini, 2020. "Identifying and measuring developments in artificial intelligence: Making the impossible possible," OECD Science, Technology and Industry Working Papers 2020/05, OECD Publishing.
    73. Xinli Wang & Yuansheng Huang, 2021. "The heterogeneous impact of environmental regulations on low‐carbon economic transformation in China: Empirical research based on the mediation effect model," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 11(1), pages 81-102, February.
    74. 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).
    75. 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).
    76. Li, Guoxiang & Wu, Haoyue & Jiang, Jieshu & Zong, Qingqing, 2023. "Digital finance and the low-carbon energy transition (LCET) from the perspective of capital-biased technical progress," Energy Economics, Elsevier, vol. 120(C).
    77. Qiang Wang & Jie Fan & Mei-Po Kwan & Kan Zhou & Guofeng Shen & Na Li & Bowei Wu & Jian Lin, 2023. "Examining energy inequality under the rapid residential energy transition in China through household surveys," Nature Energy, Nature, vol. 8(3), pages 251-263, March.
    78. Hao, Xiaoli & Deng, Feng, 2019. "The marginal and double threshold effects of regional innovation on energy consumption structure: Evidence from resource-based regions in China," Energy Policy, Elsevier, vol. 131(C), pages 144-154.
    79. Mariani, Marcello M. & Machado, Isa & Magrelli, Vittoria & Dwivedi, Yogesh K., 2023. "Artificial intelligence in innovation research: A systematic review, conceptual framework, and future research directions," Technovation, Elsevier, vol. 122(C).
    80. Daron Acemoglu & Pascual Restrepo, 2020. "Robots and Jobs: Evidence from US Labor Markets," Journal of Political Economy, University of Chicago Press, vol. 128(6), pages 2188-2244.
    81. Mamidi, Varsha & Marisetty, Vijaya B. & Thomas, Ewan Nikhil, 2021. "Clean energy transition and intertemporal socio-economic development: Evidence from an emerging market," Energy Economics, Elsevier, vol. 101(C).
    82. Tao, Weiliang & Weng, Shimei & Chen, Xueli & ALHussan, Fawaz Baddar & Song, Malin, 2024. "Artificial intelligence-driven transformations in low-carbon energy structure: Evidence from China," Energy Economics, Elsevier, vol. 136(C).
    83. 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).
    84. Debnath, Kumar Biswajit & Mourshed, Monjur, 2018. "Forecasting methods in energy planning models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 297-325.
    85. Jeff Borland & Michael Coelli, 2017. "Are Robots Taking Our Jobs?," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 50(4), pages 377-397, December.
    86. Zheng, Xuemei & Zou, Fenju & Liu, Ziwei & Nepal, Rabindra, 2025. "How does digitalization affect capacity utilization in the energy sector? Evidence from China," Energy Economics, Elsevier, vol. 144(C).
    87. Sanya Carley, 2011. "The Era of State Energy Policy Innovation: A Review of Policy Instruments," Review of Policy Research, Policy Studies Organization, vol. 28(3), pages 265-294, May.
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