Leveraging AI to Assess Supply Chain Vulnerabilities and Enhance Resilience Against External Shocks

Abstract

Supply chains are increasingly complex and interconnected, making them vulnerable to a wide range of external shocks such as natural disasters, geopolitical tensions, and pandemics. Leveraging artificial intelligence (AI) offers a transformative approach to assess these vulnerabilities and enhance supply chain resilience. This paper explores the application of AI in identifying, analyzing, and mitigating risks within supply chains, focusing on predictive analytics, real-time monitoring, and adaptive response strategies. AI-driven predictive analytics enable the anticipation of disruptions by analyzing vast amounts of data from diverse sources, including weather patterns, social media trends, and economic indicators. Machine learning algorithms can detect patterns and forecast potential disruptions, allowing companies to proactively adjust their operations. Real-time monitoring through AI technologies such as Internet of Things (IoT) sensors and blockchain ensures continuous visibility across the supply chain, providing immediate alerts to emerging issues and enabling swift corrective actions. This dynamic adaptability is crucial for mitigating the impact of unexpected shocks and sustaining supply chain performance. The integration of AI also enhances collaboration and communication among supply chain stakeholders. AI-powered platforms can streamline information sharing and decision-making processes, fostering a more resilient and responsive supply chain network. AI provides a powerful toolkit for assessing supply chain vulnerabilities and enhancing resilience against external shocks. Future research should focus on developing more sophisticated AI models and exploring their practical applications across different industries to fully realize the potential of AI in supply chain management.