IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v85y2025ipds1544612325013911.html

Artificial intelligence and the quality of corporate accounting information disclosure

Author

Listed:
  • Yang, Tongshu
  • Zhou, Nina

Abstract

This study draws on data from companies listed on the Shenzhen Stock Exchange in China from 2014 to 2023 to examine the impact of artificial intelligence (AI) adoption on the quality of corporate accounting information disclosure, along with its heterogeneity and underlying mechanisms. The baseline results show that AI adoption significantly enhances disclosure quality. Heterogeneity analysis finds this positive effect is more evident in small- and medium-sized enterprises, firms in central cities, and high-tech industries. Mechanism analysis indicates that improvements in the business environment and increases in corporate growth potential further amplify AI’s positive impact. This study provides empirical evidence on AI’s role in improving accounting information quality and offers theoretical insights and practical guidance for policymakers and corporate managers seeking to implement AI effectively.

Suggested Citation

  • Yang, Tongshu & Zhou, Nina, 2025. "Artificial intelligence and the quality of corporate accounting information disclosure," Finance Research Letters, Elsevier, vol. 85(PD).
    • Handle: RePEc:eee:finlet:v:85:y:2025:i:pd:s1544612325013911
    DOI: 10.1016/j.frl.2025.108136
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612325013911
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2025.108136?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. Edward Elson Kosasih & Emmanuel Papadakis & George Baryannis & Alexandra Brintrup, 2024. "A review of explainable artificial intelligence in supply chain management using neurosymbolic approaches," International Journal of Production Research, Taylor & Francis Journals, vol. 62(4), pages 1510-1540, February.
    2. Yang, Chih-Hai, 2022. "How Artificial Intelligence Technology Affects Productivity and Employment: Firm-level Evidence from Taiwan," Research Policy, Elsevier, vol. 51(6).
    3. Silvana Secinaro & Davide Calandra & Federico Lanzalonga & Paolo Biancone, 2024. "The Role of Artificial Intelligence in Management Accounting: An Exploratory Case Study," Springer Books, in: Arif Perdana & Tawei Wang (ed.), Digital Transformation in Accounting and Auditing, chapter 0, pages 207-236, Springer.
    4. Ma, Jinghao & Shang, Yujie & Liang, Zhenghan, 2025. "Digital transformation, artificial intelligence and enterprise innovation performance," Finance Research Letters, Elsevier, vol. 78(C).
    5. Mohamed Nofel & Mahmoud Marzouk & Hany Elbardan & Reda Saleh & Aly Mogahed, 2024. "Integrating Blockchain, IoT, and XBRL in Accounting Information Systems: A Systematic Literature Review," JRFM, MDPI, vol. 17(8), pages 1-32, August.
    6. Patricia M. Dechow & Richard G. Sloan & Amy P. Sweeney, 1996. "Causes and Consequences of Earnings Manipulation: An Analysis of Firms Subject to Enforcement Actions by the SEC," Contemporary Accounting Research, John Wiley & Sons, vol. 13(1), pages 1-36, March.
    7. Chen, Jia & Wang, Ning & Lin, Tongzhi & Liu, Baoliu & Hu, Jin, 2024. "Shock or empowerment? Artificial intelligence technology and corporate ESG performance," Economic Analysis and Policy, Elsevier, vol. 83(C), pages 1080-1096.
    8. Roppelt, Julia Stefanie & Kanbach, Dominik K. & Kraus, Sascha, 2024. "Artificial intelligence in healthcare institutions: A systematic literature review on influencing factors," Technology in Society, Elsevier, vol. 76(C).
    9. Moustafa Al Najjar & Mohamed Gaber Ghanem & Rasha Mahboub & Bilal Nakhal, 2024. "The Role of Artificial Intelligence in Eliminating Accounting Errors," JRFM, MDPI, vol. 17(8), pages 1-15, August.
    10. Ida Merete Enholm & Emmanouil Papagiannidis & Patrick Mikalef & John Krogstie, 2022. "Artificial Intelligence and Business Value: a Literature Review," Information Systems Frontiers, Springer, vol. 24(5), pages 1709-1734, October.
    11. Nam Hoang Vu & Tram Bao Hoang & Duong Tung Bui & Quan Hong Nguyen, 2024. "Integration into global value chains and firm innovation: does local business environment matter?," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 51(4), pages 725-791, December.
    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. Wang, Zheng & Liu, Hongchao, 2026. "Artificial intelligence and the historical performance expectation gap: Evidence from the moderating role of monetary easing," Economic Analysis and Policy, Elsevier, vol. 89(C), pages 1077-1092.

    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. Yao, Nengzhi(Chris) & Bai, Junhong & Yu, Zihao & Guo, Qiaozhe, 2025. "Does AI orientation facilitate operational efficiency? A contingent strategic orientation perspective," Journal of Business Research, Elsevier, vol. 186(C).
    2. Wu, Yulin & Zhang, Jiahui & Cai, Xinyu, 2025. "Impact of regional artificial intelligence development on corporate environmental information," Finance Research Letters, Elsevier, vol. 80(C).
    3. Liu, Hongjiao, 2025. "Artificial intelligence development and household financial asset allocation," International Review of Economics & Finance, Elsevier, vol. 102(C).
    4. Shi, Renbo & Shan, Wei & Evans, Richard & Wang, Qingjin, 2025. "Artificial intelligence-driven energy technology innovation: Dynamic impact and mechanism exploration," Energy Economics, Elsevier, vol. 147(C).
    5. Tao Chen & Shuwen Pi & Qing Sophie Wang, 2025. "Artificial Intelligence and Corporate Investment Efficiency: Evidence from Chinese Listed Companies," Working Papers in Economics 25/05, University of Canterbury, Department of Economics and Finance.
    6. Anup Banerjee & Mattias Nordqvist & Karin Hellerstedt, 2020. "The role of the board chair—A literature review and suggestions for future research," Corporate Governance: An International Review, Wiley Blackwell, vol. 28(6), pages 372-405, November.
    7. Carlos Jiménez-Angueira & Nathan Stuart, 2015. "Relative performance evaluation, pay-for-luck, and double-dipping in CEO compensation," Review of Quantitative Finance and Accounting, Springer, vol. 44(4), pages 701-732, May.
    8. Spira, Robin, 2024. "How does ESG rating disagreement influence analyst forecast dispersion?," Junior Management Science (JUMS), Junior Management Science e. V., vol. 9(3), pages 1769-1804.
    9. repec:rjr:romjef:v::y:2025:i:3:p:5-23 is not listed on IDEAS
    10. Hanish Rajpal & Pawan Jain, 2018. "Auditor’s Characteristics and Earnings Management in India," Accounting and Finance Research, Sciedu Press, vol. 7(4), pages 1-43, November.
    11. Basil Al‐Najjar, 2012. "The determinants of board meetings: evidence from categorical analysis," Journal of Applied Accounting Research, Emerald Group Publishing Limited, vol. 13(2), pages 178-190, September.
    12. Jong Chool Park & Qiang Wu, 2009. "Financial Restatements, Cost of Debt and Information Spillover: Evidence From the Secondary Loan Market," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 36(9‐10), pages 1117-1147, November.
    13. Ararat, Melsa & Yurtoglu, B. Burcin, 2021. "Female directors, board committees, and firm performance: Time-series evidence from Turkey," Emerging Markets Review, Elsevier, vol. 48(C).
    14. Joan Torrent‐Sellens & Mihaela Enache‐Zegheru & Pilar Ficapal‐Cusí, 2025. "Promoting the European Sustainable Firm: How Economic, Social, and Green Innovation and the AI‐Based Technologies Create Pathways of Social and Environmental Sustainability," Business Strategy and the Environment, Wiley Blackwell, vol. 34(7), pages 9093-9119, November.
    15. Hessian, Mohamed & Zalata, Alaa Mansour & Hussainey, Khaled, 2025. "Does the board of directors and their stock ownership mitigate interest payment classification shifting? UK evidence," Journal of International Accounting, Auditing and Taxation, Elsevier, vol. 58(C).
    16. 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.
    17. Wang, Tracy Yue & Winton, Andrew, 2021. "Industry informational interactions and corporate fraud," Journal of Corporate Finance, Elsevier, vol. 69(C).
    18. Carol Liu, M.H. & Zhuang, Zili, 2011. "Management earnings forecasts and the quality of analysts’ forecasts: The moderating effect of audit committees," Journal of Contemporary Accounting and Economics, Elsevier, vol. 7(1), pages 31-45.
    19. Curtis Nicholls, 2016. "The impact of SEC investigations and accounting and auditing enforcement releases on firms’ cost of equity capital," Review of Quantitative Finance and Accounting, Springer, vol. 47(1), pages 57-82, July.
    20. Zvi Singer & Jing Zhang, 2022. "Do companies try to conceal financial misstatements through auditor shopping?," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 49(1-2), pages 140-180, January.
    21. Miao, Miao & Yang, Yuxuan & Li, Xueyao & He, Wenjian, 2025. "Bankruptcy judicial reform and corporate fraud: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 103(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:finlet:v:85:y:2025:i:pd:s1544612325013911. 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.