admin@publications.scrs.in   
Advancements in Intelligent Systems

The Convergence of Intelligent Systems and SAP Solutions: Shaping the Future of Enterprise Resource Planning

Authors: Chetan Sharma, Rohini Sharma and Kavita Sharma


Publishing Date: 16-01-2025

ISBN: 978-81-975670-3-2

DOI: https://doi.org/10.56155/978-81-975670-3-2-6

Abstract

In recent years, intelligent systems like artificial intelligence (AI), machine learning (ML), and advanced data analytics have greatly improved SAP solutions used in enterprise resource planning (ERP) and business management. This article looks at different types of intelligent technologies, such as natural language processing (NLP) and robotic process automation (RPA), and how they integrate with SAP systems. It also highlights specific products like SAP Leonardo and SAP AI. The study discusses how these intelligent systems boost efficiency, improve decision-making, and enhance overall organizational performance through real-time data processing, predictive analytics, and automation. However, there are challenges, such as data privacy issues, the need for significant investment in technology, and the continuous need for employee skill development. The proposed methodology includes analyzing case studies and empirical data to show the strategic importance of intelligent systems in modern SAP solutions. The article also explores future prospects, suggesting that using these systems can give organizations a competitive edge and drive innovation and efficiency in the dynamic digital economy.

Keywords

SAP; ERP; S/4HANA; SAP Analytic Cloud; Cloud Computing; Intelligent Systems; Artificial Intelligence; Machine Learning; NLP; RPA; SAP Data Intelligence; SAP Cloud Platform

Cite as

Chetan Sharma, Rohini Sharma and Kavita Sharma, "The Convergence of Intelligent Systems and SAP Solutions: Shaping the Future of Enterprise Resource Planning", In: Harish Sharma, Chetan Sharma and Vaishali Maheshwari (eds), Advancements in Intelligent Systems, SCRS, India, 2025, pp. 71-93. https://doi.org/10.56155/978-81-975670-3-2-6

Recent