Unpacking organisational ambidexterity as a dynamic capability: a microfoundational approach in artificial intelligence innovation ecosystems

Purpose This study aims to investigate how organisational ambidexterity operates as a higher-order dynamic capability in the context of artificial intelligence (AI), with a specific focus on its microfoundations within innovation ecosystems (IEs). Design/methodology/approach Adopting a qualitative case study approach, the research analyses a leading organisation orchestrator of an AI IE. Drawing on in-depth interviews and Gioia methodology, the study identifies the routines, practices and roles that enable the organisation to balance exploration and exploitation across multiple levels within ecosystems. Findings The findings demonstrate that organisations can enact ambidexterity through a set of nine microfoundations that underpin sensing, seizing and transforming capabilities across individual, interactional and structural dimensions. Together, these mechanisms foster adaptability, integration and learning within a complex, evolving ecosystem. The study extends the dynamic capabilities framework by offering a granular account of how ambidexterity is operationalised in IEs. Practical implications The research provides actionable insights for managers navigating digital complexity, particularly in ecosystems shaped by AI. It emphasises the need to cultivate ambidextrous routines, invest in adaptive platforms and support boundary-spanning roles that enable continuous learning, cross-functional coordination and strategic responsiveness. Originality/value This study contributes to the literature on dynamic capabilities and ambidexterity by empirically grounding their microfoundations in the underexplored context of AI IEs. It offers a multi-level perspective on how organisations orchestrate knowledge flows, align digital architectures and mobilise hybrid roles to sustain innovation performance in rapidly changing technological environments.