Artificial intelligence, dynamic capabilities, and innovation resilience: The contingent roles of market competition intensity and technological turbulence

This study examines how artificial intelligence (AI) improves innovation resilience via dynamic capabilities (DCs) and the contingent mechanisms of market competition intensity and technological turbulence, integrating the resource-based view (RBV), dynamic capabilities theory (DCT), and contingency theory. A conceptual framework was empirically tested using a fixed-effect model and an instrumental variable 2SLS model on data collected from 3958 A-share companies listed in China from 2011 to 2023. The results show that AI and DCs had a significant impact on enterprise innovation resilience, with the effect of AI on innovation resilience being approximately 50%. In particular, AI enhanced innovation elasticity through DCs, especially absorptive capability. Further analysis reveals that both the intensity of market competition and technological turbulence significantly weakened the positive impact of AI on innovation resilience, thereby supporting the contingent view of environmental-technological adaptation. This study expands the value realization path of strategic resources in the RBV from the perspective of digitalized scenarios and DCs. Additionally, it strengthens the understanding of how AI can transform into innovation resilience based on contingency theory. This research offers significant implications, providing valuable insights for scholars and policymakers seeking to optimize the deployment of AI and formulate effective policies.