IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v86y2025ipes1544612325019063.html

Intelligent governance? Evidence from the adoption of AI in Chinese A-share firms

Author

Listed:
  • Chen, Lusi
  • Yang, Kun
  • Yu, Fangkun

Abstract

In the context of China’s rapidly evolving digital transformation and increasingly complex economic environment, enterprises’ governance challenges have intensified, making it urgent to explore the influence of artificial intelligence (AI) on enhancing corporate governance. Using panel data of Chinese A-share listed firms from 2010 to 2023, this study empirically examines the impact of AI adoption on governance quality. The results reveal that AI significantly improves governance outcomes, with internal control serving as a key mediating mechanism. Moreover, higher industry competition enhances this positive effect, and it also becomes more pronounced in technology-intensive sectors. These findings remain robust across a variety of empirical tests. This study makes three notable contributions. First, it extends the literature by correlating AI adoption with corporate governance rather than solely performance or innovation. Second, it demonstrates the mechanism of internal control in shaping governance outcomes. Third, it reveals the contingent influence of industry characteristics. The results provide practical insights for firms and regulators, indicating that AI should be strategically deployed in governance areas with high information asymmetry and monitoring costs, while regulatory standards should be updated to ensure transparency, accountability, and resilience in AI-assisted governance systems.

Suggested Citation

  • Chen, Lusi & Yang, Kun & Yu, Fangkun, 2025. "Intelligent governance? Evidence from the adoption of AI in Chinese A-share firms," Finance Research Letters, Elsevier, vol. 86(PE).
    • Handle: RePEc:eee:finlet:v:86:y:2025:i:pe:s1544612325019063
    DOI: 10.1016/j.frl.2025.108652
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612325019063
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2025.108652?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. Rammer, Christian & Fernández, Gastón P. & Czarnitzki, Dirk, 2022. "Artificial intelligence and industrial innovation: Evidence from German firm-level data," Research Policy, Elsevier, vol. 51(7).
    2. Jie Cheng & Nai Ru Xu & Noor Ullah Khan & Harcharanjit Singh Mahinder Singh, 2025. "The impacts of artificial intelligence literacy, green absorptive capacity, and green information system on green innovation," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 32(2), pages 2375-2389, March.
    3. Yang, Chih-Hai, 2022. "How Artificial Intelligence Technology Affects Productivity and Employment: Firm-level Evidence from Taiwan," Research Policy, Elsevier, vol. 51(6).
    4. Michael C. Jensen, 2010. "The Modern Industrial Revolution, Exit, and the Failure of Internal Control Systems," Journal of Applied Corporate Finance, Morgan Stanley, vol. 22(1), pages 43-58, January.
    5. Cheng, Xuanmei & Du, Anna Min & Yan, Chengnuo & Goodell, John W., 2025. "Internal business process governance and external regulation: How does AI technology empower financial performance?," International Review of Financial Analysis, Elsevier, vol. 99(C).
    6. Sullivan, Yulia & Fosso Wamba, Samuel, 2024. "Artificial intelligence and adaptive response to market changes: A strategy to enhance firm performance and innovation," Journal of Business Research, Elsevier, vol. 174(C).
    7. Lu, Chia-Hui, 2021. "The impact of artificial intelligence on economic growth and welfare," Journal of Macroeconomics, Elsevier, vol. 69(C).
    8. Zhou, Xiaoyong & Li, Gaochao & Wang, Qunwei & Li, Yangganxuan & Zhou, Dequn, 2025. "Artificial intelligence, corporate information governance and ESG performance: Quasi-experimental evidence from China," International Review of Financial Analysis, Elsevier, vol. 102(C).
    9. Han, Qifeng & Li, Chunhui & Jin, Yulu, 2025. "The impact of intellectual property protection on the development of artificial intelligence in enterprises," International Review of Financial Analysis, Elsevier, vol. 105(C).
    10. Capatina, Alexandru & Kachour, Maher & Lichy, Jessica & Micu, Adrian & Micu, Angela-Eliza & Codignola, Federica, 2020. "Matching the future capabilities of an artificial intelligence-based software for social media marketing with potential users’ expectations," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    11. Shivam Gupta & Sachin Modgil & Samadrita Bhattacharyya & Indranil Bose, 2022. "Artificial intelligence for decision support systems in the field of operations research: review and future scope of research," Annals of Operations Research, Springer, vol. 308(1), pages 215-274, January.
    12. Westhead, Paul & Wright, Mike & Ucbasaran, Deniz, 2001. "The internationalization of new and small firms: A resource-based view," Journal of Business Venturing, Elsevier, vol. 16(4), pages 333-358, July.
    13. Chen, Pengyu & Chu, Zhongzhu & Zhao, Miao, 2024. "The Road to corporate sustainability: The importance of artificial intelligence," Technology in Society, Elsevier, vol. 76(C).
    14. Mertzanis, Charilaos, 2025. "Artificial intelligence and investment management: Structure, strategy, and governance," International Review of Financial Analysis, Elsevier, vol. 107(C).
    15. Tang, Hui-Wen & Chen, Anlin, 2020. "How do market power and industry competition influence the effect of corporate governance on earnings management?," The Quarterly Review of Economics and Finance, Elsevier, vol. 78(C), pages 212-225.
    16. Gao, Yang & Liu, Siqiang & Yang, Lu, 2025. "Artificial intelligence and innovation capability: A dynamic capabilities perspective," International Review of Economics & Finance, Elsevier, vol. 98(C).
    17. Ali Meftah Gerged, 2021. "Factors affecting corporate environmental disclosure in emerging markets: The role of corporate governance structures," Business Strategy and the Environment, Wiley Blackwell, vol. 30(1), pages 609-629, January.
    18. 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.
    19. Tan, Jianhua & Chang, Samuel & Zheng, Ying & Chan, Kam C., 2025. "Effects of artificial intelligence in the modern business: Client artificial intelligence application and audit quality," International Review of Financial Analysis, Elsevier, vol. 104(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. Wu, Yulin & Zhang, Jiahui & Cai, Xinyu, 2025. "Impact of regional artificial intelligence development on corporate environmental information," Finance Research Letters, Elsevier, vol. 80(C).
    2. Li, Zhe & Liu, Minggang & Wang, Lu, 2025. "Artificial intelligence development and rural labor employment quality," International Review of Economics & Finance, Elsevier, vol. 102(C).
    3. Wu, Weiwei & Zhang, Yifan, 2025. "Artificial intelligence innovation and environmental performance: Unraveling the complex roles of application and method innovation across enterprise sizes," Technological Forecasting and Social Change, Elsevier, vol. 218(C).
    4. Wang, Liangcheng & Chen, Yizheng, 2025. "Artificial intelligence and corporate investment efficiency: Evidence from China," Emerging Markets Review, Elsevier, vol. 68(C).
    5. Dong, Feng & Zhao, Xu & Mangla, Sachin Kumar & Song, Malin, 2025. "Enhanced supply chain resilience under geopolitical risks: The role of artificial intelligence," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 202(C).
    6. Flavio Spagnuolo & Raffaela Casciello & Ilaria Martino & Fiorenza Meucci, 2025. "Exploring the impact of artificial intelligence on the pursuit of SDGs: Evidence from European state‐owned enterprises," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 32(2), pages 1987-2001, March.
    7. Liu, Hongjiao, 2025. "Artificial intelligence development and household financial asset allocation," International Review of Economics & Finance, Elsevier, vol. 102(C).
    8. Zhang, Chen & Li, Rongrong & Wang, Qiang, 2026. "Artificial intelligence and sustainable development: A global nonlinear analysis of the moderating roles of human capital and renewable energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 228(C).
    9. Ma, Yuan & Zhang, Wenchao & Ma, Chengxiang & Ai, Yudong & Hu, Jun, 2025. "Artificial intelligence, data elements, digital economy, and corporate innovation performance," International Review of Economics & Finance, Elsevier, vol. 103(C).
    10. Boqiang Lin & Yitong Zhu, 2025. "Does AI elevate corporate ESG performance? A supply chain perspective," Business Strategy and the Environment, Wiley Blackwell, vol. 34(1), pages 586-597, January.
    11. repec:rjr:romjef:v::y:2025:i:3:p:5-23 is not listed on IDEAS
    12. Czarnitzki, Dirk & Fernández, Gastón P. & Rammer, Christian, 2023. "Artificial intelligence and firm-level productivity," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 188-205.
    13. Dong, Li & Liu, Junxian & Yang, Jinghan & Zhang, Xin, 2025. "The deployment of general large language models and corporate value: Evidence from the stock market," Finance Research Letters, Elsevier, vol. 86(PD).
    14. Standaert, Thomas & Andries, Petra, 2026. "Overcoming difficulties in knowledge transfer: Harnessing the power of AI to drive process innovation," Technovation, Elsevier, vol. 149(C).
    15. Flavio Calvino & Luca Fontanelli, 2026. "Decoding AI: an early look at how French firms use AI," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 16(1), pages 51-93, March.
    16. Zhao, Lang & Xu, Jiawei & Zhang, Baofeng & Lu, Jianjun, 2026. "Leveraging AI to enhance firms’ resource efficiency: ecological modernization theory and resource-based view perspectives," International Journal of Production Economics, Elsevier, vol. 291(C).
    17. Nils Grashof & Alexander Kopka, 2023. "Widening or closing the gap? The relationship between artificial intelligence, firm-level productivity and regional clusters," Bremen Papers on Economics & Innovation 2304, University of Bremen, Faculty of Business Studies and Economics.
    18. Yuanhe Du & Tianhang Liu & Wei Shang & Jia Li, 2025. "Research on the Impact of Artificial Intelligence on Urban Green Energy Efficiency: An Empirical Test Based on Neural Network Models," Sustainability, MDPI, vol. 17(16), pages 1-47, August.
    19. Sullivan, Yulia & Fosso Wamba, Samuel, 2024. "Artificial intelligence and adaptive response to market changes: A strategy to enhance firm performance and innovation," Journal of Business Research, Elsevier, vol. 174(C).
    20. 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.
    21. Zhang, Yujie & Ba, Zhichao & Mao, Jin & Li, Gang, 2025. "Quantifying the impact of digital technology on enterprise processes using LLM-based causal claim networks," Journal of Informetrics, Elsevier, vol. 19(3).

    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:finlet:v:86:y:2025:i:pe:s1544612325019063. 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/frl .

    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.