IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v140y2024ics0140988324006960.html
   My bibliography  Save this article

The impact of artificial intelligence on the energy transition: The role of regulatory quality as a guardrail, not a wall

Author

Listed:
  • Dong, Zequn
  • Tan, Chaodan
  • Ma, Biao
  • Ning, Zhaoshuo

Abstract

In recent years, the economic impact and environmental contribution of Artificial Intelligence (AI) have gradually become a new focus in academia. This study uses a panel data sample of 50 countries to explore the impact of AI on energy transition (ET), aiming to fill an important research gap. The results highlight several critical insights. First, AI has had a significant positive impact on facilitating the ET. This conclusion still holds after a series of robustness tests. Second, AI positively affects ET by promoting renewable energy technology innovation and upgrading the electricity structure, resulting in both technological and structural effects. Third, the impact of AI on ET is non-linear. Threshold effect models show that AI impacts ET differently at various levels of regulation quality (RQ), exhibiting a double threshold effect. AI hinders ET when RQ is lower than the first threshold value. When RQ is in the second range, AI significantly facilitates ET. However, when RQ exceeds the second threshold value, AI hinders ET again. These findings provide insights into the mechanisms of AI's impact on ET and emphasize that an appropriate level of regulation is crucial for AI to facilitate ET. Finally, this study analyzes heterogeneity and offers targeted policy recommendations.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:eneeco:v:140:y:2024:i:c:s0140988324006960
    DOI: 10.1016/j.eneco.2024.107988
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988324006960
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eneco.2024.107988?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Pata, Ugur Korkut & Alola, Andrew Adewale & Erdogan, Sinan & Kartal, Mustafa Tevfik, 2023. "The influence of income, economic policy uncertainty, geopolitical risk, and urbanization on renewable energy investments in G7 countries," Energy Economics, Elsevier, vol. 128(C).
    2. Yi, Jiahui & Dai, Sheng & Li, Lin & Cheng, Jinhua, 2024. "How does digital economy development affect renewable energy innovation?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    3. Opeyemi, Akinyemi & Uchenna, Efobi & Simplice, Asongu & Evans, Osabuohein, 2019. "Renewable energy, trade performance and the conditional role of finance and institutional capacity in sub-Sahara African countries," Energy Policy, Elsevier, vol. 132(C), pages 490-498.
    4. Wei, Jia & Wen, Jun & Wang, Xiao-Yang & Ma, Jie & Chang, Chun-Ping, 2023. "Green innovation, natural extreme events, and energy transition: Evidence from Asia-Pacific economies," Energy Economics, Elsevier, vol. 121(C).
    5. Dong, Zequn & Tan, Chaodan & Zhang, Wenxue & Zhang, Lixiang & Zhang, Lingran, 2024. "Are natural resources a blessing or a curse for renewable energy? Uncovering the role of regulatory quality and government effectiveness in mitigating the curse," Resources Policy, Elsevier, vol. 98(C).
    6. 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).
    7. 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).
    8. 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).
    9. Bruce E. Hansen, 2000. "Sample Splitting and Threshold Estimation," Econometrica, Econometric Society, vol. 68(3), pages 575-604, May.
    10. 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).
    11. Srivastava, Praveen Ranjan & Mangla, Sachin Kumar & Eachempati, Prajwal & Tiwari, Aviral Kumar, 2023. "An explainable artificial intelligence approach to understanding drivers of economic energy consumption and sustainability," Energy Economics, Elsevier, vol. 125(C).
    12. Lahouar, A. & Ben Hadj Slama, J., 2017. "Hour-ahead wind power forecast based on random forests," Renewable Energy, Elsevier, vol. 109(C), pages 529-541.
    13. Ebeke, Christian & Omgba, Luc Désiré & Laajaj, Rachid, 2015. "Oil, governance and the (mis)allocation of talent in developing countries," Journal of Development Economics, Elsevier, vol. 114(C), pages 126-141.
    14. Shahbaz, Muhammad & Wang, Jianda & Dong, Kangyin & Zhao, Jun, 2022. "The impact of digital economy on energy transition across the globe: The mediating role of government governance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).
    15. Chishti, Muhammad Zubair & Xia, Xiqiang & Dogan, Eyup, 2024. "Understanding the effects of artificial intelligence on energy transition: The moderating role of Paris Agreement," Energy Economics, Elsevier, vol. 131(C).
    16. 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).
    17. Kaller, Alexander & Bielen, Samantha & Marneffe, Wim, 2018. "The impact of regulatory quality and corruption on residential electricity prices in the context of electricity market reforms," Energy Policy, Elsevier, vol. 123(C), pages 514-524.
    18. Hansen, Bruce E., 1999. "Threshold effects in non-dynamic panels: Estimation, testing, and inference," Journal of Econometrics, Elsevier, vol. 93(2), pages 345-368, December.
    19. Wang, Qiang & Dong, Zequn & Li, Rongrong & Wang, Lili, 2022. "Renewable energy and economic growth: New insight from country risks," Energy, Elsevier, vol. 238(PC).
    20. 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).
    21. 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).
    22. repec:hal:pseose:halshs-01112661 is not listed on IDEAS
    23. 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).
    24. Giorgio Calcagnini & Germana Giombini & Giuseppe Travaglini, 2018. "A Schumpeterian model of investment and innovation with labor market regulation," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 27(7), pages 628-651, October.
    25. Du, Juntao & Shen, Zhiyang & Song, Malin & Vardanyan, Michael, 2023. "The role of green financing in facilitating renewable energy transition in China: Perspectives from energy governance, environmental regulation, and market reforms," Energy Economics, Elsevier, vol. 120(C).
    26. Bellakhal, Rihab & Ben Kheder, Sonia & Haffoudhi, Houda, 2019. "Governance and renewable energy investment in MENA countries:How does trade matter?," Energy Economics, Elsevier, vol. 84(C).
    27. 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).
    28. Ghoddusi, Hamed & Creamer, Germán G. & Rafizadeh, Nima, 2019. "Machine learning in energy economics and finance: A review," Energy Economics, Elsevier, vol. 81(C), pages 709-727.
    29. Afolabi, Joshua Adeyemi, 2023. "Natural resource rent and environmental quality nexus in Sub-Saharan Africa: Assessing the role of regulatory quality," Resources Policy, Elsevier, vol. 82(C).
    30. Yin, Zi Hui & Zeng, Wei Ping, 2023. "The effects of industrial intelligence on China's energy intensity: The role of technology absorptive capacity," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    31. Danish & Recep Ulucak & Salah Ud‐Din Khan & Muhammad Awais Baloch & Nan Li, 2020. "Mitigation pathways toward sustainable development: Is there any trade‐off between environmental regulation and carbon emissions reduction?," Sustainable Development, John Wiley & Sons, Ltd., vol. 28(4), pages 813-822, July.
    32. 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.
    33. Lee, Chien-Chiang & Yuan, Zihao & Lee, Chi-Chuan & Chang, Yu-Fang, 2022. "The impact of renewable energy technology innovation on energy poverty: Does climate risk matter?," Energy Economics, Elsevier, vol. 116(C).
    34. 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).
    35. Xu, Si & Zhang, You & Chen, Lan & Leong, Lin Woon & Muda, Iskandar & Ali, Anis, 2023. "How Fintech and effective governance derive the greener energy transition: Evidence from panel-corrected standard errors approach," Energy Economics, Elsevier, vol. 125(C).
    36. Zahoor Ahmed & Mahmood Ahmad & Husam Rjoub & Olga A. Kalugina & Nazim Hussain, 2022. "Economic growth, renewable energy consumption, and ecological footprint: Exploring the role of environmental regulations and democracy in sustainable development," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(4), pages 595-605, August.
    37. 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).
    38. 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).
    39. Sinha, Avik & Bekiros, Stelios & Hussain, Nazim & Nguyen, Duc Khuong & Khan, Sana Akbar, 2023. "How social imbalance and governance quality shape policy directives for energy transition in the OECD countries?," Energy Economics, Elsevier, vol. 120(C).
    40. 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).
    41. Chen, Yang & Cheng, Liang & Lee, Chien-Chiang, 2022. "How does the use of industrial robots affect the ecological footprint? International evidence," Ecological Economics, Elsevier, vol. 198(C).
    42. 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).
    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. Hafize Nurgul Durmus Senyapar & Ramazan Bayindir, 2025. "The Energy Hunger Paradox of Artificial Intelligence: End of Clean Energy or Magic Wand for Sustainability?," Sustainability, MDPI, vol. 17(7), pages 1-32, March.

    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. 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).
    2. 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).
    3. Chishti, Muhammad Zubair & Xia, Xiqiang & Dogan, Eyup, 2024. "Understanding the effects of artificial intelligence on energy transition: The moderating role of Paris Agreement," Energy Economics, Elsevier, vol. 131(C).
    4. Li, Lanbing & Zhao, Jiawei & Yang, Yuhan & Ma, Dan, 2025. "Artificial intelligence and green development well-being: Effects and mechanisms in China," Energy Economics, Elsevier, vol. 141(C).
    5. 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).
    6. Lee, Chien-Chiang & Wang, Tianhui, 2024. "The impact of renewable energy policies on the energy transition -– An empirical analysis of Chinese cities," Energy Economics, Elsevier, vol. 138(C).
    7. 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).
    8. Dong, Zequn & Tan, Chaodan & Zhang, Wenxue & Zhang, Lixiang & Zhang, Lingran, 2024. "Are natural resources a blessing or a curse for renewable energy? Uncovering the role of regulatory quality and government effectiveness in mitigating the curse," Resources Policy, Elsevier, vol. 98(C).
    9. Jiao, Anqi & Lu, Juntai & Ren, Honglin & Wei, Jia, 2024. "The role of AI capabilities in environmental management: Evidence from USA firms," Energy Economics, Elsevier, vol. 134(C).
    10. 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).
    11. Wang, Yong & Zhao, Wenhao & Ma, Xuejiao, 2024. "The spatial spillover impact of artificial intelligence on energy efficiency: Empirical evidence from 278 Chinese cities," Energy, Elsevier, vol. 312(C).
    12. 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).
    13. Lee, Chien-Chiang & Yan, Jingyang, 2024. "Will artificial intelligence make energy cleaner? Evidence of nonlinearity," Applied Energy, Elsevier, vol. 363(C).
    14. 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.
    15. 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).
    16. 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).
    17. Lin, Boqiang & Xu, Chongchong, 2024. "The effects of industrial robots on firm energy intensity: From the perspective of technological innovation and electrification," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    18. 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).
    19. 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).
    20. Zhang, Dongyang, 2024. "The pathway to curb greenwashing in sustainable growth: The role of artificial intelligence," Energy Economics, Elsevier, vol. 133(C).

    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:140:y:2024:i:c:s0140988324006960. 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.