Artificial Intelligence and Business Model Innovation: A Dynamic Capabilities Explanation
Keywords:
artificial intelligence, business model innovation, dynamic capabilities, digital transformation, strategic renewal, AI-enabled capabilitiesAbstract
This study examines how artificial intelligence (AI) drives business model innovation (BMI) by addressing the fragmented theoretical understanding of the relationship between technological capabilities and strategic transformation. While prior research highlights AI’s role in enhancing data-driven decision-making and innovation outcomes, it provides limited explanation of the mechanisms through which AI capabilities reshape business model architectures. Drawing on the dynamic capabilities perspective, this article develops a mechanism-based conceptual framework explaining how AI-enabled sensing, seizing, and reconfiguring processes mediate the relationship between AI capabilities and systemic business model reconfiguration. Using theory synthesis and integrative conceptual analysis, the study bridges literature on AI capabilities, business model innovation, and dynamic capabilities. The proposed framework conceptualizes AI as an enabling organizational capability that strengthens opportunity recognition, supports data-driven strategic experimentation, and facilitates the reconfiguration of value creation, delivery, and capture mechanisms. The study contributes by advancing a process-oriented explanation of AI-driven BMI, integrating previously disconnected research streams, and developing testable theoretical propositions. Beyond theoretical contributions, the framework offers implications for managers and policymakers seeking to leverage AI for sustainable digital transformation, particularly in advancing innovation-driven economic growth and adaptive organizational systems.
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