Industry 4.0 (I4.0) is causing significant changes in the competitive dynamics of various economic sectors. Technological advances driven by I4.0 in supply chain management (SCM) have been the subject of comprehensive study both in academia and in industry. SCM plays a fundamental role in enhancing operational efficiency, promoting customer satisfaction, reducing costs, and adapting to market changes. Bringing these perspectives into the business context, the acronym VUCA (Volatility; Uncertainty; Complexity; and Ambiguity), which describes a volatile, uncertain, complex, and ambiguous world, becomes considerably relevant. Additionally, highly improbable and unpredictable events, known as Black Swans, such as COVID-19 and the war between Russia and Ukraine, further exacerbate the uncertain scenario. Focusing on the defense sector presents additional challenges, given the unique circumstances associated with defending a country. In this challenging scenario, among the technologies introduced by I4.0 with application in SCM, Artificial Intelligence (AI) stands out for the strategic differentiation it provides to adopters. AI plays a central role in the digital transformation process of any organization. Thus, the objective of this research is to identify and evaluate the adoption of AI in the performance and resilience of the national defense supply chain. To this end, a mixed research methodology was used, starting with a scoping review that identified the state of the art and future trends of I4.0 in the defense sector SCM, culminating in the development of a research agenda composed of 4 clusters. Next, a systematic literature review was conducted to identify and analyze the factors affecting the adoption of AI in the defense sector based on the findings of the scoping review and highly relevant articles on the researched theme, resulting in the formulation of constructs and variables related to the factors influencing AI adoption and how this technology impacts the supply chain. As a third research method, a survey was conducted in the defense sector with the purpose of identifying and empirically evaluating the adoption of AI in the performance and resilience of the supply chain. Descriptive and exploratory factor analyses of the data were performed, resulting in 6 latent factors composed of variables with higher factor loadings and allowing for the formulation of new constructs and variables that now await confirmatory analysis through future research. Finally, the research proposes a roadmap to strengthen and improve the performance of the Defense industry supply chain using AI. This new artifact was developed through an approach that combines different methods, such as bibliometric analysis, systematic review, and questionnaires, to understand and explore the challenges. To demonstrate its practical application, the plan was adapted for the Brazilian Navy, highlighting how AI can be used in planning and goal execution to increase the robustness, resilience, and responsiveness (Triple-R) of the supply chain, considering both the technical and social aspects of the institutional context. Furthermore, the theoretical research resulted in a future research agenda on digital transformation in the defense industry, outlining a path for the development of innovative solutions guided by the adoption of AI.