Supported use cases for SAP AI Joule

Authors

  • Ankit Kumar Gupta Uttar Pradesh Technical University, Lucknow, Uttar Pradesh, India. Author

DOI:

https://doi.org/10.47392/IRJAEH.2025.0303

Keywords:

SAP AI Joule, Enterprise AI Copilot, Generative AI, Conversational AI, Intelligent Automation, ERP Systems; Explainable AI, Business Process Optimization, AI Governance, Autonomous Enterprise

Abstract

In industrial environments, unexpected machinery failures can result in expensive downtime along with SAP AI Joule marks a pivotal advancement in enterprise AI, serving as a dynamic copilot that augments user productivity, enhances decision-making accuracy, and accelerates workflow automation across SAP’s cloud portfolio. By embedding generative AI and conversational interfaces into core business applications, Joule is redefining how enterprise users interact with data and processes. This review synthesizes Joule’s supported use cases, experimental impacts, architectural principles, and prevailing challenges. While early results are promising, sustained success will depend on advancements in AI transparency, domain adaptation, ethical governance, and scalability. Future research must prioritize explainable AI, federated learning approaches, and dynamic adaptability to truly unlock Joule’s transformative potential for the intelligent enterprise.

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Published

2025-05-05

How to Cite

Supported use cases for SAP AI Joule. (2025). International Research Journal on Advanced Engineering Hub (IRJAEH), 3(05), 2075-2081. https://doi.org/10.47392/IRJAEH.2025.0303

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