IDEAS home Printed from https://ideas.repec.org/a/jbh/ijsrcs/v11y2025i2id1555.html

Conversational AI for Enterprise Data Analytics and Governance: A Comprehensive Framework for Natural Language-Driven Business Intelligence

Author

Listed:
  • Venkat Sanka

Abstract

The integration of conversational artificial intelligence into enterprise data analytics and governance represents a paradigm shift in how organizations interact with their data assets. This paper presents a comprehensive framework for implementing conversational AI systems that enable natural language querying, automated compliance monitoring, and intelligent data discovery in enterprise environments. The proposed architecture leverages advanced natural language processing techniques, including large language models and context-aware dialogue systems, to bridge the gap between business users and complex data infrastructures. Through empirical evaluation across three enterprise domains— financial services, healthcare, and telecommunications—the framework demonstrates significant improvements in query response time (67% reduction), user adoption rates (89% increase), and data governance compliance (78% improvement). The system addresses critical challenges including query ambiguity resolution, multi-modal data integration, and real-time governance policy enforcement. Results indicate that conversational AI can effectively democratize data access while maintaining stringent security and compliance requirements, positioning it as a transformative technology for enterprise data management.

Suggested Citation

  • Venkat Sanka, 2025. "Conversational AI for Enterprise Data Analytics and Governance: A Comprehensive Framework for Natural Language-Driven Business Intelligence," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 11(2), pages 3922-3928, March.
  • Handle: RePEc:jbh:ijsrcs:v11:y2025:i2:id:1555
    DOI: 10.32628/CSEIT25111329
    Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT25111329
    as

    Download full text from publisher

    File URL: https://ijsrcseit.com/home/article/view/CSEIT25111329
    File Function: Article URL
    Download Restriction: no

    File URL: https://ijsrcseit.com/home/article/download/CSEIT25111329/CSEIT25111329
    File Function: Full text
    Download Restriction: no

    File URL: https://libkey.io/10.32628/CSEIT25111329?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
    ---><---

    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:jbh:ijsrcs:v11:y2025:i2:id:1555. 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: Pankaj Sharma (USA) (email available below). General contact details of provider: https://ijsrcseit.com/home .

    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.