OPTIMIZING DECISION-MAKING IN SUPPLY CHAINS: A FRAMEWORK FOR AI AND HUMAN COLLABORATION USING SAP TECHNOLOGIES - KarthikSai Chenna, (INTERNATIONAL JOURNAL OF RESEARCH IN COMPUTER APPLICATIONS AND INFORMATION TECHNOLOGY (IJRCAIT), 2024)
This article examines the transformative impact of integrating Artificial Intelligence (AI) with human expertise in SAP-based supply chain management systems. Through an analysis of current implementations and case studies, we explore how AI-driven tools enhance data analytics, predictive modeling, and automated decision-making while human managers provide crucial contextual knowledge and strategic oversight. The article highlights key benefits, including improved demand forecasting accuracy, increased operational efficiency, and enhanced supply chain agility. We also address critical challenges such as data quality management, system integration, and organizational change. Our findings suggest that the synergy between AI capabilities and human judgment creates a robust framework for optimizing supply chain performance in dynamic business environments. This article proposes a collaborative model that leverages SAP's AI-powered solutions alongside human expertise to achieve a more resilient and responsive supply chain. The article contributes to the growing body of literature on AI applications in supply chain management. It offers practical insights for organizations seeking to implement or improve AI-human collaborative systems within their SAP-based supply chain operations.