Artificial Intelligence-Enabled Maritime Supply Chain Resilience: A Systematic Literature Review

Maritime supply chains are exposed to pandemics, geopolitical conflict, extreme weather, congestion, equipment failure, and cyberattacks. This review examines how artificial intelligence (AI) supports resilience across maritime supply chains. The Web of Science Core Collection was searched on 26 August 2026 using intersecting AI, resilience, and maritime supply chain terms. The search yielded 336 English-language records. After temporal consistency checks, 328 publications from 2018–2026 formed the common corpus for bibliometric and systematic content analysis; seven earlier studies were consulted as intellectual foundations, and one record assigned to 2027 was excluded. CiteSpace mapping, structured coding, and conceptual synthesis produced four findings. First, publication output accelerated after 2023, and domain-informed coding of the keyword network identified seven connected themes spanning predictive intelligence, data infrastructure, operations, coordination, risk, and sustainability. Second, the literature concentrates on operational disruption, safety, and cyber risk and applies machine learning, deep learning, and reinforcement learning mainly to vessel and port operations. Third, the synthesis suggests that AI contributes to resilience indirectly: model outputs must become organizational capabilities and enter strategies such as resource reallocation, substitution, and network reconfiguration before they can influence resistance, recovery, adaptation, or transformation. Fourth, much of the evidence remains based on single-site data, simulation, or routine operating conditions rather than on causal evaluation during actual disruptions. The review therefore proposes a theory-informed framework linking shocks, AI technologies, organizational capabilities, resilience strategies, outcomes, and boundary conditions.