IDEAS home Printed from https://ideas.repec.org/a/das/njaigs/v8y2025i1p241-257id382.html
   My bibliography  Save this article

Leveraging Sap Joule AI for Autonomous Business Process Optimization In 2025

Author

Listed:
  • Sankar Thambireddy
  • Venkata Ramana Reddy Bussu
  • Arunkumar Pasumarthi

Abstract

With a fast-changing digital environment and an added desire among businesses to achieve efficient operations and reduce costs, artificial intelligence (AI) is becoming a necessary component within enterprise resource planning (ERP) systems. Encompassing an innovative solution of SAP Joule AI, the possibility of an autonomous system optimization of business processes is given due to machine learning, predictive analytics, and real-time data processing. This paper discusses how SAP Joule AI could change business processes in various industries in 2025, especially its ability to automate business and decision-making processes and improve operational efficiency. An in-depth analysis of its technological base, the implementation approaches, and the expected financial implications for the business, this paper presents a usable perspective of how SAP Joule AI will transform the future of enterprise systems. Reading the case studies and investigating the new trends offers practical knowledge to businesses that need to remain competitive in an environment that is getting more AI-driven.

Suggested Citation

  • Sankar Thambireddy & Venkata Ramana Reddy Bussu & Arunkumar Pasumarthi, 2025. "Leveraging Sap Joule AI for Autonomous Business Process Optimization In 2025," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 8(1), pages 241-257.
  • Handle: RePEc:das:njaigs:v:8:y:2025:i:1:p:241-257:id:382
    as

    Download full text from publisher

    File URL: https://newjaigs.com/index.php/JAIGS/article/view/382
    Download Restriction: no
    ---><---

    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:das:njaigs:v:8:y:2025:i:1:p:241-257:id:382. 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: Open Knowledge (email available below). General contact details of provider: https://newjaigs.com/index.php/JAIGS/ .

    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.