Supply Chain Risk Management: Leveraging AI for Risk Identification, Mitigation, and Resilience Planning
https://doi.org/10.62157/ijietom.v2i2.38
Keywords:
Supply chain risk management, Artificial intelligence, Risk identification, Resilience planning, Predictive analytics, Disruption managementAbstract
This study explores the critical role of Supply Chain Risk Management (SCRM) in today's interconnected and dynamic global economy, focusing on leveraging Artificial Intelligence (AI) for risk identification, mitigation, and resilience planning. As supply chains face increasing vulnerabilities due to geopolitical tensions, natural disasters, and technological disruptions, traditional risk-management approaches have proven insufficient in addressing these challenges. This paper comprehensively analyses how AI, through predictive analytics, machine learning, and autonomous systems, transforms SCRM by enabling real-time risk detection and response capabilities. The study also examines AI applications across various industries, including manufacturing, retail, and logistics, showcasing its potential in optimizing operational efficiency, enhancing supply chain visibility, and improving decision-making processes. Furthermore, the paper highlights the benefits and limitations of integrating AI with emerging technologies such as IoT and blockchain to enhance supply chain resilience. The findings contribute to understanding AI's growing impact on global supply chain management, providing insights into future trends and practical recommendations for managers seeking to strengthen their risk management strategies.
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