Leveraging AI and Machine Learning in SAP S/4HANA Cloud: A Research-Based Approach to Supply Chain Optimization

Authors

  • Satheesh Kumar Nendrambaka Cognizant Technology Solutions U.S. Corporation, USA Author

DOI:

https://doi.org/10.32628/CSEIT241061232

Keywords:

Supply Chain Optimization, Artificial Intelligence Integration, SAP S/4HANA Cloud, Predictive Analytics, Enterprise Resource Planning (ERP) Transformation

Abstract

This article examines the transformative impact of Artificial Intelligence (AI) and Machine Learning (ML) integration within SAP S/4HANA Cloud for supply chain optimization. Through a comprehensive article analysis of multiple enterprise-level implementations conducted over an extended period, the study investigates the effectiveness of AI-driven solutions in enhancing supply chain visibility, operational efficiency, and decision-making capabilities. The article employs a mixed-methods approach, combining quantitative performance metrics with qualitative stakeholder insights to evaluate the implementation outcomes and strategic benefits. The article reveals substantial improvements across multiple dimensions, including significant reductions in operational costs, manual interventions, and marked enhancement in order fulfillment accuracy. The article also addresses critical implementation considerations, including change management strategies, best practices, and potential challenges in AI integration. Furthermore, the article explores emerging trends and future implications for supply chain management, including the role of quantum computing, edge processing, and digital twins. This comprehensive article analysis provides valuable insights for organizations seeking to leverage AI and ML capabilities in their supply chain operations, while also contributing to the broader understanding of digital transformation in enterprise resource planning systems.

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References

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Published

18-12-2024

Issue

Section

Research Articles

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