IDEAS home Printed from https://ideas.repec.org/a/jbh/ijsrcs/v11y2025i2id1143.html

AI Transformation in JD Edwards EnterpriseOne: A Technical Deep Dive

Author

Listed:
  • Shyamlal Sama

Abstract

The integration of Artificial Intelligence (AI) with JD Edwards EnterpriseOne (JDE E1) represents a transformative evolution in Enterprise Resource Planning (ERP) systems, fundamentally changing how organizations manage their business processes. This technical article explores the comprehensive impact of AI integration across various functional domains of JDE E1, examining both the technological requirements and organizational implications. It investigates core AI technologies enhancing JDE E1, including predictive analytics and machine learning implementations while analyzing the architectural considerations necessary for successful integration. The article delves into practical applications across financial operations, supply chain optimization, and manufacturing intelligence, providing insights into how AI transforms these critical business functions. It also addresses implementation considerations, emphasizing technical prerequisites and integration strategies essential for successful AI adoption. Furthermore, the article examines future trends in natural language processing, advanced automation, and cognitive services, offering organizations a roadmap for leveraging AI capabilities within their JDE E1 environments to achieve improved operational efficiency and competitive advantage.

Suggested Citation

  • Shyamlal Sama, 2025. "AI Transformation in JD Edwards EnterpriseOne: A Technical Deep Dive," 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 720-728, March.
  • Handle: RePEc:jbh:ijsrcs:v11:y2025:i2:id:1143
    DOI: 10.32628/CSEIT251112381
    Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT251112381
    as

    Download full text from publisher

    File URL: https://ijsrcseit.com/home/article/view/CSEIT251112381
    File Function: Article URL
    Download Restriction: no

    File URL: https://ijsrcseit.com/home/article/download/CSEIT251112381/CSEIT251112381
    File Function: Full text
    Download Restriction: no

    File URL: https://libkey.io/10.32628/CSEIT251112381?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:1143. 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.