Architecting Intelligent Enterprise Applications: AI and ML Convergence within SAP S/4HANA Ecosystem

Authors

  • Venu Gopal Avula Independent Researcher, USA
  • Surya Narayana Chakka Independent Researcher, USA
  • Mohamed Abdul Kadar Mohamed Jabarullah Independent Researcher, USA

Keywords:

Artificial Intelligence, Machine Learning, SAP S / S/4HANA Enterprise Application, Digital Transformation, Business Optimization, ERP Systems

Abstract

When applied in the SAP S/4HANA ecosystem, Artificial Intelligence and Machine Learning have become the focal points of the progress of modern enterprise applications. The paper explores the potential of combining AI and ML to enhance business efficiency, inform decision-making, and optimize enterprise operations within the SAP S/4HANA system. This paper aims to explore the opportunities and challenges associated with implementing these technologies in SAP S/4HANA ERP systems. Employing the performance and case study methods, the study examines the role of AI and ML in operational efficiency and innovation. As the results show, combining AI and ML solutions into SAP S/4HANA can considerably expand its capabilities and lead to elevated agility, scalability, and overall business performance. The paper concludes with practical suggestions for organizations to maximize the benefits of AI and ML, enabling them to thrive in a digital-first world.

Published

12-02-2022

How to Cite

Venu Gopal Avula, Surya Narayana Chakka, & Mohamed Abdul Kadar Mohamed Jabarullah. (2022). Architecting Intelligent Enterprise Applications: AI and ML Convergence within SAP S/4HANA Ecosystem. Well Testing Journal, 31(1), 169–184. Retrieved from https://welltestingjournal.com/index.php/WT/article/view/196

Issue

Section

Original Research Articles

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