IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v148y2025ics0140988325003482.html

The impact of artificial intelligence policy on green innovation of firms

Author

Listed:
  • Lin, Boqiang
  • Zhu, Yitong

Abstract

As a pivotal force in driving innovation, Artificial Intelligence (AI) has played a significant role in the technological advancement of enterprises. Investigating the impact of AI pilot policies on corporate green innovation is not only conducive to optimizing the development trajectory of AI but also an essential measure in advancing sustainable development strategies. This study uses the 2019 Chinese AI Innovation and Development Pilot Zone (AIP) policy as a quasi-natural experiment, examining the influence of policy on corporate green innovation and its intrinsic mechanisms of action. The findings indicate: (1) The AIP policy significantly fosters green innovation among enterprises in the pilot regions, with results remaining robust after a series of sensitivity tests; (2) Mechanism analysis reveals that the influence of the policy on corporate green innovation is mediated by R&D investment and is also moderated by the level of ESG and environmental disclosure; (3) Heterogeneity tests discover that the policy has a more pronounced impact on enterprises with superior financing conditions, lower market concentration, and higher levels of regional digital economic development. This paper not only provides theoretical support for understanding the role of AI in corporate green development but also offers empirical references for assessing the policy effects of AI development.

Suggested Citation

  • Lin, Boqiang & Zhu, Yitong, 2025. "The impact of artificial intelligence policy on green innovation of firms," Energy Economics, Elsevier, vol. 148(C).
  • Handle: RePEc:eee:eneeco:v:148:y:2025:i:c:s0140988325003482
    DOI: 10.1016/j.eneco.2025.108524
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988325003482
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eneco.2025.108524?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. Nishant, Rohit & Kennedy, Mike & Corbett, Jacqueline, 2020. "Artificial intelligence for sustainability: Challenges, opportunities, and a research agenda," International Journal of Information Management, Elsevier, vol. 53(C).
    2. 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).
    3. Nie, Jing & Zhang, Jiaming & Chang, Xue, 2024. "Does social capital matter to firm digital transformation? Evidence from China," Finance Research Letters, Elsevier, vol. 65(C).
    4. Lara Waltersmann & Steffen Kiemel & Julian Stuhlsatz & Alexander Sauer & Robert Miehe, 2021. "Artificial Intelligence Applications for Increasing Resource Efficiency in Manufacturing Companies—A Comprehensive Review," Sustainability, MDPI, vol. 13(12), pages 1-26, June.
    5. Horbach, Jens & Rammer, Christian & Rennings, Klaus, 2012. "Determinants of eco-innovations by type of environmental impact — The role of regulatory push/pull, technology push and market pull," Ecological Economics, Elsevier, vol. 78(C), pages 112-122.
    6. Yang, Chih-Hai, 2022. "How Artificial Intelligence Technology Affects Productivity and Employment: Firm-level Evidence from Taiwan," Research Policy, Elsevier, vol. 51(6).
    7. Xie, Xiaoyu & Yan, Jun, 2024. "How does artificial intelligence affect productivity and agglomeration? Evidence from China's listed enterprise data," International Review of Economics & Finance, Elsevier, vol. 94(C).
    8. Wu, Haitao & Hao, Yu & Ren, Siyu, 2020. "How do environmental regulation and environmental decentralization affect green total factor energy efficiency: Evidence from China," Energy Economics, Elsevier, vol. 91(C).
    9. 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).
    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, Siquan & Du, Anna Min & Lin, Boqiang, 2025. "Micro-mechanisms of digitalization-driven financing for renewable energy: Growing capital pools and shifting flows," Research in International Business and Finance, Elsevier, vol. 73(PA).
    12. Jiatao Li & Han Jiang & Jia Shen & Haoyuan Ding & Rongjian Yu, 2024. "Using the difference-in-differences design with panel data in international business research: progress, potential issues, and practical suggestions," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 55(8), pages 949-961, October.
    13. Wang, Siquan & Du, Anna Min & Lin, Boqiang, 2025. "Market mechanisms for energy transition: Fossil energy price shocks and irrational renewable energy financing," Journal of International Money and Finance, Elsevier, vol. 151(C).
    14. Fu, Yanyu, 2024. "Enterprises’ internationalization, R&D investment and enterprise performance," Finance Research Letters, Elsevier, vol. 67(PA).
    15. Li, Changsong & Cao, Xiaojing & Wang, Zeyu & Zhang, Jiali & Liu, Huan, 2025. "The impact of green bond issuance on corporate green innovation: A signaling perspective," International Review of Financial Analysis, Elsevier, vol. 102(C).
    16. Beladi, Hamid & Deng, Jie & Hu, May, 2021. "Cash flow uncertainty, financial constraints and R&D investment," International Review of Financial Analysis, Elsevier, vol. 76(C).
    17. Hao, Yu & Gai, Zhiqiang & Wu, Haitao, 2020. "How do resource misallocation and government corruption affect green total factor energy efficiency? Evidence from China," Energy Policy, Elsevier, vol. 143(C).
    18. Murtaza Hussain & Shaohua Yang & Umer Sahil Maqsood & R. M. Ammar Zahid, 2024. "Tapping into the green potential: The power of artificial intelligence adoption in corporate green innovation drive," Business Strategy and the Environment, Wiley Blackwell, vol. 33(5), pages 4375-4396, July.
    19. Dou, Weijian & Zhang, Han & Miao, Bowen & Wang, Bin, 2025. "How do analyst attention and green credit promote corporate green innovation?," International Review of Economics & Finance, Elsevier, vol. 99(C).
    20. Zhong, Kai & Song, Liangrong, 2025. "Artificial intelligence adoption and corporate green innovation capability," Finance Research Letters, Elsevier, vol. 72(C).
    21. Liu, Jianing & Long, Fenjie & Chen, Lei & Li, Lei & Zheng, Longfei & Mi, Zhifu, 2025. "Exploratory or exploitative green innovation? The role of different green fiscal policies in motivating innovation," Technovation, Elsevier, vol. 143(C).
    22. Xu, Bin & Lin, Boqiang, 2025. "How does green credit effectively promote green technology innovation?," International Review of Financial Analysis, Elsevier, vol. 102(C).
    23. Wang, Linhui & Chen, Qi & Dong, Zhiqing & Cheng, Lu, 2024. "The role of industrial intelligence in peaking carbon emissions in China," Technological Forecasting and Social Change, Elsevier, vol. 199(C).
    24. Michael E. Porter & Claas van der Linde, 1995. "Toward a New Conception of the Environment-Competitiveness Relationship," Journal of Economic Perspectives, American Economic Association, vol. 9(4), pages 97-118, Fall.
    25. Daron Acemoglu & Philippe Aghion & Leonardo Bursztyn & David Hemous, 2012. "The Environment and Directed Technical Change," American Economic Review, American Economic Association, vol. 102(1), pages 131-166, February.
    26. 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).
    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. Cheng, Jixin & Yang, Dingjian & Xu, Lan, 2025. "Digital economy, technical progress reversal, and climate change governance–insights on digital technology and data factor," Energy Economics, Elsevier, vol. 150(C).
    2. Chen, Yuhang & Zhong, Yilin & Xu, Feng & Zhang, Qinghua, 2025. "Driving environmental, social, and governance excellence: The direct and indirect effects of intelligent transformation," Structural Change and Economic Dynamics, Elsevier, vol. 75(C), pages 313-331.
    3. Wang, Yang & Wang, Yongheng & Yang, Pengyu, 2025. "Does artificial intelligence impact corporate ESG performance? Evidence from a quasi-natural experiment in China," Energy Economics, Elsevier, vol. 151(C).
    4. Lin, Boqiang & Zhou, Dengli, 2025. "A new green transition driver: How does artificial intelligence affect the green economic efficiency," Energy, Elsevier, vol. 334(C).

    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. Zhang, Fuyu & Wang, Qiang & Li, Rongrong, 2025. "How does clean energy reshape the relationship between artificial intelligence and carbon emissions? Evidence from renewable and nuclear energy," Energy Economics, Elsevier, vol. 149(C).
    2. 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).
    3. 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).
    4. Liu, Qilu & Du, Shanshan & Li, Min, 2025. "Green innovation perspective: Artificial intelligence and corporate green development," International Review of Economics & Finance, Elsevier, vol. 102(C).
    5. 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).
    6. 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).
    7. Torrent-Sellens, Joan & Enache-Zegheru, Mihaela & Ficapal-Cusí, Pilar, 2025. "Twin transitions or a meeting of strangers? Unravelling the effects of AI and innovations on economic, social and environmental MSMEs sustainability," Technology in Society, Elsevier, vol. 81(C).
    8. 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.
    9. Xie, Li & Li, Siyi, 2024. "Climate risk and energy-saving technology innovation: Evidence from Chinese prefecture-level cities," Energy Economics, Elsevier, vol. 139(C).
    10. Horbach, Jens & Rammer, Christian, 2025. "Climate change affectedness and innovation in firms," Research Policy, Elsevier, vol. 54(1).
    11. Wu, Yulin & Zhang, Jiahui & Cai, Xinyu, 2025. "Impact of regional artificial intelligence development on corporate environmental information," Finance Research Letters, Elsevier, vol. 80(C).
    12. Chen, Lusi & Li, Shinan & She, Zhili, 2025. "A study on the impact of artificial intelligence applications on corporate green technological innovation: A mechanism analysis from multiple perspectives," International Review of Economics & Finance, Elsevier, vol. 103(C).
    13. Renfei, Chen & Zhongwen, Li & Guangfei, Yang & Wenli, Li & Zitong, Guo, 2026. "Exploring how artificial intelligence capabilities impact corporate sustainability performance: Insights from Chinese manufacturing firms," Technovation, Elsevier, vol. 149(C).
    14. Zu, Xu & Ni, Guangxian & Hu, Ruifeng, 2025. "AI technology innovation, knowledge management and corporate environmental sustainability: Evidence from Chinese patent data," Technology in Society, Elsevier, vol. 83(C).
    15. Song, Wenfei & Han, Xianfeng & Liu, Qiange, 2024. "Patterns of environmental regulation and green innovation in China," Structural Change and Economic Dynamics, Elsevier, vol. 71(C), pages 176-192.
    16. Xie, Ronghui & Teo, Thompson S.H., 2022. "Green technology innovation, environmental externality, and the cleaner upgrading of industrial structure in China — Considering the moderating effect of environmental regulation," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    17. Zhou, Kuo & Luo, Haotian & Qu, Zhi, 2023. "What can the environmental rule of law do for environmental innovation? Evidence from environmental tribunals in China," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    18. Liu, Guanchun & Zhang, Gaorong & Song, Malin & Fu, Shun, 2025. "Carbon emissions trading and corporate energy efficiency: Evidence from a quasi-natural experiment in China," Technological Forecasting and Social Change, Elsevier, vol. 212(C).
    19. Lu, Yue & Ma, Minghui & Wei, Yaning & Zhang, Yue, 2025. "Artificial intelligence, global value chain position and manufacturing firm emissions," Structural Change and Economic Dynamics, Elsevier, vol. 75(C), pages 815-827.
    20. Song, Yang & Zhang, Yue & Zhang, Zhipeng & Sahut, Jean-Michel, 2025. "Artificial intelligence, digital finance, and green innovation," Global Finance Journal, Elsevier, vol. 64(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:148:y:2025:i:c:s0140988325003482. 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.