Omnichannel, Resilience, and Artificial Intelligence in the Supply Chain: a Bibliometric Analysis (2019–2026) and an Integrative Framework

Objective: To map the intellectual and thematic structure of research on omnichannel (2019–2026) and, based on the identified themes, propose an integrative framework that connects omnichannel, supply chain resilience, and artificial intelligence (AI) without multiplying risks. Methods: A mixed-methods study combining bibliometric analysis—according to Donthu et al. (2021), based on a corpus of 2,869 journal articles extracted from the OpenAlex open-access database and selected using PRISMA—with performance analysis and scientific mapping, and the deductive construction of a conceptual framework based on the identified gaps. Results and Conclusion: Output grew from 99 articles (2019) to 813 (2025), totaling 26,161 citations; The United States, Indonesia, China, and India lead; and the thematic structure reveals a core focused on customer experience and channel integration, an axis centered on supply chain and logistics, and a cluster related to digital transformation, while AI and resilience remain emerging areas. In light of this gap, a four-layer framework is proposed—data sources, real-time integration, intelligence, and decision-making, under cross-functional governance—from which three management principles are derived: visibility with verification prior to automation; AI as augmentation, not replacement; and the primacy of competencies and coordination. Research Implications: The study provides a current overview of the field and a structured tool for managing the risks created by integration, with socio-environmental and sector-specific implications. Originality/Value: It links empirical evidence on the structure of the field to a conceptual framework, articulating omnichannel, resilience, and AI—which are usually treated in isolation—and reframing integration as a system that simultaneously mitigates and generates risks.