This chapter evaluates the promises and limitations of applying artificial intelligence in humanitarian supply chains, which coordinate the delivery of life-saving goods and services during crises. It explores how AI-driven tools can support decision-making in disaster relief and global health logistics—for example, by improving demand forecasting for emergency supplies, optimizing distribution routes under unstable conditions, and aiding coordination among relief agencies. These potential benefits are illustrated through scenarios such as vaccine distribution and disaster response, where AI could enhance speed and efficiency. At the same time, the chapter critically examines the significant challenges and constraints in these settings that can hinder AI’s impact. Humanitarian operations often face severe data scarcity, rapidly changing environments, and the need for transparency and trust, which make many AI models difficult to implement effectively. We discuss issues such as unreliable or biased data, the importance of interpretability of AI recommendations for critical decisions, and the necessity of human oversight. By weighing these factors, the chapter provides a nuanced perspective on AI’s role in humanitarian logistics. It concludes that while AI has the potential to greatly improve humanitarian supply chain performance, realizing this potential requires careful alignment of technology with on-the-ground expertise, ethical considerations, and robust infrastructure in crisis environments.