Global supply chains are increasingly vulnerable to turbulence caused by changing customer demands, rapid technological advancements, and unpredictable disruptions. Drawing on the dynamic capabilities view and organizational information processing theory, this study examines how market dynamism influences the adoption of artificial intelligence and supply chain resilience, with a particular focus on cross-national differences between the United States and Korea. Using survey data from 297 firms and employing partial least squares structural equation modeling with multigroup analysis, the study highlights the role of resilience in translating environmental turbulence and technological adoption into performance outcomes. Overall, market dynamism positively impacts AI adoption and resilience, and AI adoption significantly enhances resilience. Multigroup analysis reveals notable contextual differences: U.S. firms respond more directly to market dynamism by adopting AI and improving their resilience, whereas Korean firms rely more heavily on AI adoption to develop resilience after implementing the technology. A moderation analysis further reveals that market dynamism strengthens the effect of AI adoption on firm performance, underscoring the contextual nature of AI-enabled resilience. The findings refine the dynamic capabilities view by showing that capability deployment effectiveness is context-dependent rather than universal, and they extend organizational information processing theory by conceptualizing AI as an adaptive mechanism shaped by institutional and technological conditions.