International Research Journal of Engineering and Technology (IRJET) Volume: 11 Issue: 07 | July 2024
www.irjet.net
e-ISSN: 2395-0056 p-ISSN: 2395-0072
Super Intelligent Supply Chains: Harnessing AI & SAP for NextGen Transportation Efficiency Sudhir Makkar Accenture, Washington DC, USA ***
Abstract: Supply chain management continues to revolutionize by integrating Artificial Intelligence (AI) with SAP's cutting-edge Transportation Management ™ systems. This study investigates how AI-trained models and algorithms enhance supply chain efficiency, visibility, and decision-making when coupled with SAP TM. SAP TM can better plan routes, forecast demand, reduce risks, and optimize costs by utilizing finetuned AI models. This results in significant cost savings, improved service standards, and higher customer satisfaction (CSAT) scores for firms of all sizes. We will also delve into novel and innovative features of SAP Joule with Embedded AI and highlight how they affect supply chains and impact transportation for organizations. We will also explore into potential advantages, and challenges that AI poses vis-à-vis integration with SAP TM and future trends using an extensive literature review, a methodological framework, and the examination of case studies. Multiple case studies indicate that while AI and TM integration offers numerous advantages, challenges such as cost, training of AI models, and siloed data complexities still need to be addressed. This paper aims to provide valuable insights for industry practitioners and researchers on the transformative potential of AI in SAP TM and its implications for the future of supply chain management. Keywords: AI, SAP Joule, SAP TM, Planning and Optimization, Embedded Analytics, Supply Chain Management
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