IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v143y2025ics0140988325000544.html
   My bibliography  Save this article

The impact of artificial intelligence on the energy consumption of corporations: The role of human capital

Author

Listed:
  • Lee, Chien-Chiang
  • Zou, Jinyang
  • Chen, Pei-Fen

Abstract

The rapid development of artificial intelligence (AI) has brought tremendous benefits to corporate development. However, its energy-intensive characteristic has also led to a sharp increase in corporate energy consumption (CEC). Research on how to mitigate the impact of AI on CEC is crucial. This paper utilizes text analysis to collect information on AI development from the annual reports of listed companies. Based on this information, an AI development index at the enterprise level is constructed and matched with the energy consumption data of listed companies, resulting in panel data from 2013 to 2022. Subsequently, the Panel Smooth Transition Regression (PSTR) model is employed to explore the nonlinear relationship between AI and CEC under different levels of human capital (HC). The research results indicate that when HC is at a low level, AI significantly increases CEC. After HC exceeds the threshold, the effect of AI on increasing CEC is weakened, but it still contributes to an increase. These results remain valid after a series of robustness checks. The results of heterogeneity tests show that an increase in HC can also lead AI to reduce the consumption of high-pollution energy. The human capital effects and AI's technological progress effects are more pronounced in state-owned enterprises and enterprises in the high-tech industry. This paper provides theoretical support for the notion that HC can promote AI development and reduce AI's energy consumption in enterprises.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:eneeco:v:143:y:2025:i:c:s0140988325000544
    DOI: 10.1016/j.eneco.2025.108231
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988325000544
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eneco.2025.108231?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. Qin, Weiwei, 2024. "How to unleash frugal innovation through internet of things and artificial intelligence: Moderating role of entrepreneurial knowledge and future challenges," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    2. Song, Malin & Pan, Heting & Shen, Zhiyang & Tamayo-Verleene, Kristine, 2024. "Assessing the influence of artificial intelligence on the energy efficiency for sustainable ecological products value," Energy Economics, Elsevier, vol. 131(C).
    3. Bianchi, Nicola & Lu, Yi & Song, Hong, 2022. "The effect of computer-assisted learning on students’ long-term development," Journal of Development Economics, Elsevier, vol. 158(C).
    4. González, Andrés & Teräsvirta, Timo & van Dijk, Dick & Yang, Yukai, 2005. "Panel Smooth Transition Regression Models," SSE/EFI Working Paper Series in Economics and Finance 604, Stockholm School of Economics, revised 11 Oct 2017.
    5. 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).
    6. Zhang, Mingming & Zhang, Shichang & Lee, Chien-Chiang & Zhou, Dequn, 2021. "Effects of trade openness on renewable energy consumption in OECD countries: New insights from panel smooth transition regression modelling," Energy Economics, Elsevier, vol. 104(C).
    7. Yongrong Xin & Aftab Hussain Tabasam & Zhenling Chen & Aysha Zamir & Carlos Samuel Ramos-Meza, 2024. "Correction: Analyzing the Impact of Foreign Direct Investment, Energy Consumption on Services Exports, and Growth of the Services Sector: Evidence from SAARC Countries," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(3), pages 15450-15451, September.
    8. Degirmenci, Tunahan & Aydin, Mehmet & Cakmak, Bunyamin Yasin & Yigit, Busra, 2024. "A path to cleaner energy: The nexus of technological regulations, green technological innovation, economic globalization, and human capital," Energy, Elsevier, vol. 311(C).
    9. Chiu, Yi-Bin & Lee, Chien-Chiang, 2020. "Effects of financial development on energy consumption: The role of country risks," Energy Economics, Elsevier, vol. 90(C).
    10. Lee, Chien-Chiang & Chiu, Yi-Bin, 2011. "Electricity demand elasticities and temperature: Evidence from panel smooth transition regression with instrumental variable approach," Energy Economics, Elsevier, vol. 33(5), pages 896-902, September.
    11. Kong, Dongmin & Zhang, Bohui & Zhang, Jian, 2022. "Higher education and corporate innovation," Journal of Corporate Finance, Elsevier, vol. 72(C).
    12. Xu, Ru-Yu & Wang, Ke-Liang & Miao, Zhuang, 2024. "The impact of digital technology innovation on green total-factor energy efficiency in China: Does economic development matter?," Energy Policy, Elsevier, vol. 194(C).
    13. 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).
    14. 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).
    15. Zhou, Linjiang & Shi, Xiaochuan & Bao, Yaxiong & Gao, Lihua & Ma, Chao, 2023. "Explainable artificial intelligence for digital finance and consumption upgrading," Finance Research Letters, Elsevier, vol. 58(PC).
    16. Khezri, Mohsen & Mamkhezri, Jamal & Heshmati, Almas, 2024. "Exploring non-linear causal nexus between economic growth and energy consumption across various R&D regimes: Cross-country evidence from a PSTR model," Energy Economics, Elsevier, vol. 133(C).
    17. Zhang, Weike & Zeng, Ming, 2024. "Is artificial intelligence a curse or a blessing for enterprise energy intensity? Evidence from China," Energy Economics, Elsevier, vol. 134(C).
    18. Pesaran, M. Hashem & Smith, Ron, 1995. "Estimating long-run relationships from dynamic heterogeneous panels," Journal of Econometrics, Elsevier, vol. 68(1), pages 79-113, July.
    19. 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).
    20. Joaquin Vespignani & Russell Smyth, 2024. "Artificial intelligence investments reduce risks to critical mineral supply," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    21. Wang, Jianlong & Wang, Weilong & Liu, Yong & Wu, Haitao, 2023. "Can industrial robots reduce carbon emissions? Based on the perspective of energy rebound effect and labor factor flow in China," Technology in Society, Elsevier, vol. 72(C).
    22. Huang, Geng & He, Ling-Yun & Lin, Xi, 2022. "Robot adoption and energy performance: Evidence from Chinese industrial firms," Energy Economics, Elsevier, vol. 107(C).
    23. 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).
    24. Zhao, Chuan & Guo, Qidong & Jia, Rongwen & Dong, Kangyin & Wang, Kun, 2023. "How does clean energy transition promote original design manufacturers? A three-party evolutionary game analysis," Energy Economics, Elsevier, vol. 126(C).
    25. 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).
    26. Peter Dauvergne, 2022. "Is artificial intelligence greening global supply chains? Exposing the political economy of environmental costs," Review of International Political Economy, Taylor & Francis Journals, vol. 29(3), pages 696-718, May.
    27. Xi Lin & Yongle Zhao & Mahmood Ahmad & Zahoor Ahmed & Husam Rjoub & Tomiwa Sunday Adebayo, 2021. "Linking Innovative Human Capital, Economic Growth, and CO 2 Emissions: An Empirical Study Based on Chinese Provincial Panel Data," IJERPH, MDPI, vol. 18(16), pages 1-18, August.
    28. Ren, Xiaohang & Yang, Wanping & Jin, Yi, 2024. "Geopolitical risk and renewable energy consumption: Evidence from a spatial convergence perspective," Energy Economics, Elsevier, vol. 131(C).
    29. 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).
    30. Lee, Chien-Chiang & Hussain, Jafar & Abass, Qasir, 2025. "An integrated analysis of AI-driven green financing, subsidies, and knowledge to enhance CO2 reduction efficiency," Economic Analysis and Policy, Elsevier, vol. 85(C), pages 675-693.
    31. FU, Yunyun & SHEN, Yongchang & SONG, Malin & WANG, Weiyu, 2024. "Does artificial intelligence reduce corporate energy consumption? New evidence from China," Economic Analysis and Policy, Elsevier, vol. 83(C), pages 548-561.
    32. 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).
    33. Nicola Jones, 2018. "How to stop data centres from gobbling up the world’s electricity," Nature, Nature, vol. 561(7722), pages 163-166, September.
    34. Zhao, Haoran & Guo, Sen, 2023. "Analysis of the non-linear impact of digital economy development on energy intensity: Empirical research based on the PSTR model," Energy, Elsevier, vol. 282(C).
    35. Antonio Ciccone & Elias Papaioannou, 2009. "Human Capital, the Structure of Production, and Growth," The Review of Economics and Statistics, MIT Press, vol. 91(1), pages 66-82, February.
    36. Yongrong Xin & Aftab Hussain Tabasam & Zhenling Chen & Aysha Zamir & Carlos Samuel Ramos-Meza, 2024. "Analyzing the Impact of Foreign Direct Investment, Energy Consumption on Services Exports, and Growth of the Services Sector: Evidence from SAARC Countries," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(2), pages 5709-5728, June.
    37. Kopka, Alexander & Grashof, Nils, 2022. "Artificial intelligence: Catalyst or barrier on the path to sustainability?," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    38. Yi Che & Lei Zhang, 2018. "Human Capital, Technology Adoption and Firm Performance: Impacts of China's Higher Education Expansion in the Late 1990s," Economic Journal, Royal Economic Society, vol. 128(614), pages 2282-2320, September.
    39. Mat Daut, Mohammad Azhar & Hassan, Mohammad Yusri & Abdullah, Hayati & Rahman, Hasimah Abdul & Abdullah, Md Pauzi & Hussin, Faridah, 2017. "Building electrical energy consumption forecasting analysis using conventional and artificial intelligence methods: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1108-1118.
    40. Lee, Chien-Chiang & Wang, Chang-song, 2022. "Financial development, technological innovation and energy security: Evidence from Chinese provincial experience," Energy Economics, Elsevier, vol. 112(C).
    41. Zhou, Qianling & Li, Tao & Gong, Liutang, 2022. "The effect of tax incentives on energy intensity: Evidence from China's VAT reform," Energy Economics, Elsevier, vol. 108(C).
    42. Lee, Chien-Chiang & Yuan, Zihao, 2024. "Impact of energy poverty on public health: A non-linear study from an international perspective," World Development, Elsevier, vol. 174(C).
    43. Himeur, Yassine & Ghanem, Khalida & Alsalemi, Abdullah & Bensaali, Faycal & Amira, Abbes, 2021. "Artificial intelligence based anomaly detection of energy consumption in buildings: A review, current trends and new perspectives," Applied Energy, Elsevier, vol. 287(C).
    44. Chien‐Chiang Lee & Chi‐Chuan Lee & Chih‐Yang Cheng, 2022. "The impact of FDI on income inequality: Evidence from the perspective of financial development," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 137-157, January.
    45. Xiaohang Ren & Wenqi Li & Xu Cheng & Xinwei Zheng, 2024. "Economic freedom and corporate carbon emissions: International evidence," Business Strategy and the Environment, Wiley Blackwell, vol. 33(8), pages 8388-8412, December.
    46. Hou, Xiang & Hu, Qianlin & Liang, Xin & Xu, Jingxuan, 2023. "How do low-carbon city pilots affect carbon emissions? Staggered difference in difference evidence from Chinese firms," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 664-686.
    47. 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).
    48. 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).
    49. 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.
    50. 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).
    51. Dick van Dijk & Dennis Fok & Philip Hans Franses, 2005. "A multi-level panel STAR model for US manufacturing sectors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(6), pages 811-827.
    52. Zhang, Yan & Teoh, Bak Koon & Wu, Maozhi & Chen, Jiayu & Zhang, Limao, 2023. "Data-driven estimation of building energy consumption and GHG emissions using explainable artificial intelligence," Energy, Elsevier, vol. 262(PA).
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. 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).
    3. Lee, Chien-Chiang & Yan, Jingyang, 2024. "Will artificial intelligence make energy cleaner? Evidence of nonlinearity," Applied Energy, Elsevier, vol. 363(C).
    4. 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).
    5. 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).
    6. 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.
    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. Luo, Heng & Sun, Ying & Tao, Xiaosha & Tan, Wenwu & Kamarudin, Fakarudin, 2024. "Effects of global value chains on energy efficiency in G20 countries," Energy, Elsevier, vol. 313(C).
    9. Zhang, Dongyang, 2024. "The pathway to curb greenwashing in sustainable growth: The role of artificial intelligence," Energy Economics, Elsevier, vol. 133(C).
    10. Feng, Lingbing & Qi, Jiajun & Zheng, Yuhao, 2025. "How can AI reduce carbon emissions? Insights from a quasi-natural experiment using generalized random forest," Energy Economics, Elsevier, vol. 141(C).
    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. Keqi Huang & Julan Du & Jiawu Dai, 2023. "Higher education expansion and robot imports: evidence from China," Economic Change and Restructuring, Springer, vol. 56(6), pages 4339-4369, December.
    13. 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).
    14. 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).
    15. Lee, Chien-Chiang & Zou, Jinyang, 2024. "Impacts of the energy transition on public health in the context of country risk: From an international perspective," Economic Analysis and Policy, Elsevier, vol. 83(C), pages 873-895.
    16. Bai, Caiquan & Yao, Di & Xue, Qihang, 2025. "Does artificial intelligence suppress firms' greenwashing behavior? Evidence from robot adoption in China," Energy Economics, Elsevier, vol. 142(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. Manal Elhaj & Jihen Bousrih & Hind Alofaysan, 2024. "Can Technological Advancement Empower the Future of Renewable Energy? A Panel Autoregressive Distributed Lag Approach," Energies, MDPI, vol. 17(20), pages 1-18, October.
    19. Islam, Md. Monirul & Shahbaz, Muhammad & Ahmed, Faroque, 2024. "Robot race in geopolitically risky environment: Exploring the Nexus between AI-powered tech industrial outputs and energy consumption in Singapore," Technological Forecasting and Social Change, Elsevier, vol. 205(C).
    20. Guo, Qingbin & Peng, Yanqing & Luo, Kang, 2025. "The impact of artificial intelligence on energy environmental performance: Empirical evidence from cities in China," Energy Economics, Elsevier, vol. 141(C).

    More about this item

    Keywords

    Artificial intelligence; Energy consumption; Human capital; Panel smooth transition regression (PSTR) model; Text analysis;
    All these 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
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • J01 - Labor and Demographic Economics - - General - - - Labor Economics: General

    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:143:y:2025:i:c:s0140988325000544. 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.