The increasing complexity of healthcare supply chains (HSCs) has introduced significant risks, including cyber threats, disruptions, and inefficiencies. This paper explores the application of artificial intelligence (AI) and machine learning (ML) in risk management for healthcare supply chains. AI-driven models enhance predictive analytics, optimize inventory management, and mitigate disruptions by analyzing vast datasets in real time. This study reviews existing literature discusses AI-based risk assessment frameworks and presents a methodology for implementing machine learning techniques in HSC risk management. Future considerations highlight AI's role in enhancing security, resilience, and operational efficiency within healthcare logistics.
Khan et al. (Sun,) studied this question.