<![CDATA[This study examines how artificial intelligence (AI) capability is associated with business model innovation and competitive advantage in small and medium-sized enterprises (SMEs), distinguishing AI-related resources from organizational capabilities and contextual conditions. An integrative literature review synthesized 32 scholarly publications issued between 2007 and 2026, selected for their relevance to AI capability, dynamic capabilities, business model innovation, and firm performance. A theory-guided thematic synthesis organized the evidence into resource and capability foundations, organizational conversion mechanisms, boundary conditions, and strategic outcomes. The reviewed literature identifies technological infrastructure, data resources, and human expertise as important foundations of AI capability, while leadership, organizational learning, governance, and data-driven culture shape the organizational utilization of these resources. Business model innovation is identified as a potential intermediary mechanism involving changes in value proposition, value creation and delivery, and value capture. Environmental dynamism, sustainability orientation, organizational adaptability, and external integration influence the applicability of these relationships. The review develops a capability-to-business-model pathway that distinguishes AI resource foundations, capability utilization, organizational conversion processes, business model changes, and context-dependent competitive outcomes. Its contribution lies in clarifying construct boundaries and integrating previously separated explanations of AI-related organizational value in SMEs. The findings support differentiated, resource-sensitive approaches to AI adoption, although the conceptual synthesis does not establish causal effects or uniform performance benefits across firms. ]]>
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