Intercultural–AI Synergies for Supply Chain Resilience: A Bibliometric and Topic Modeling Review of Global Systems Research (2000–2025)

Supply chain resilience has become a critical capability for organizations operating in increasingly volatile global environments, where disruptions propagate rapidly across interconnected economic, technological, and cultural systems. Although artificial intelligence (AI) and intercultural competence are both recognized as strategic enablers of resilient supply chains, research examining their combined systemic impact remains fragmented. This study provides an integrated bibliometric and topic-modeling review of the literature addressing the intersection of intercultural competence, artificial intelligence, and supply chain resilience. Using bibliographic data retrieved from the Web of Science Core Collection and Scopus, we analyze scientific production, collaboration networks, conceptual clusters, and thematic trajectories through Biblioshiny and SciMAT. To capture emerging conceptual patterns, we apply LDA topic modeling, which identifies 35 latent topics subsequently organized into four higher-order macroclusters: Global Risk Systems, AI-Enabled Resilience and Predictive Systems, Human and Organizational Capabilities, and Supply Chain Resilience and Sustainable Global Operations. Results indicate a growing convergence between organizational capabilities, artificial intelligence technologies, and resilience-oriented supply chain research. While AI and resilience emerge as dominant empirical themes across the dataset, intercultural competence appears primarily as an emerging conceptual dimension associated with global coordination, cross-border collaboration, and technology adoption in multicultural environments. Accordingly, the present study interprets intercultural competence as a complementary organizational layer that may support the implementation and effectiveness of AI-enabled resilience strategies within global supply chains.