IDEAS home Printed from https://ideas.repec.org/h/spr/advbcp/978-94-6239-672-2_17.html

Research on the Integration Mechanism and Practical Path of Artificial Intelligence Empowering Intelligent Auditing Driven by Homology

Author

Listed:
  • Feilin He

    (International School of Nanjing Audit University)

Abstract

Against the backdrop of the digital economy, intelligent auditing has emerged as the core direction of digital transformation in the auditing industry. The homology between accounting and auditing provides a natural cornerstone for the construction of the intelligent auditing system. Existing research predominantly centers on the point-specific applications of artificial intelligence (AI) in auditing, with scant exploration into the in-depth coupling mechanism between homology and AI. Taking generative AI as the core, this paper elaborates on the theoretical essence of accounting-auditing homology, constructs a full-chain system of “homology foundation - technological empowerment - framework integration - path implementation”, designs core algorithm models, clarifies integration paths at the data and process levels, verifies feasibility through a case study, and proposes countermeasures for key challenges. This research breaks through the limitation of “divergence between technological application and theory”, establishes the coupling mechanism between homology and AI, provides guidance for the intelligent transformation of the industry, and contributes to enhancing the precision of enterprise risk management and control as well as the quality of information disclosure.

Suggested Citation

  • Feilin He, 2026. "Research on the Integration Mechanism and Practical Path of Artificial Intelligence Empowering Intelligent Auditing Driven by Homology," Advances in Economics, Business and Management Research,, Springer.
  • Handle: RePEc:spr:advbcp:978-94-6239-672-2_17
    DOI: 10.2991/978-94-6239-672-2_17
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    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:spr:advbcp:978-94-6239-672-2_17. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.