Healthcare organisations can be understood as knowledge ecosystems in which clinical expertise, managerial capabilities, patient experience, organisational routines, data, technologies, and inter-organisational relationships jointly shape decision-making and service delivery. Within these ecosystems, the interaction between human and artificial intelligence (AI) is transforming how knowledge is generated, shared, interpreted, and applied, with implications for healthcare innovation and multidimensional value creation. An ecosystem perspective highlights the alignment and interdependence among actors and activities involved in developing a shared value proposition (Adner, 2017; Beirão et al., 2017). The concepts of ecosystem vitality and knowledge ecology further illuminate the conditions under which these ecosystems can evolve, remain resilient, and sustain value creation over time.

AI is increasingly becoming an integral component of healthcare organisations’ cognitive architecture. From an ecology-of-knowledge perspective, it is not merely technological infrastructure or a productivity tool, but an active participant in organisational cognition alongside human minds, routines, relationships, cultural artefacts, data, and technologies. In healthcare, AI can support diagnosis, resource allocation, service design, operational planning, innovation, and strategic decision-making. Its organisational implications, however, extend beyond task automation: AI can augment human capabilities while generating tensions concerning the distribution of tasks, authority, responsibility, and control between human and artificial agents (Raisch & Krakowski, 2021; Lee & Yoon, 2021).

Against this background, the Track examines how humans and AI interact within healthcare knowledge ecosystems and how these interactions contribute to innovation and multidimensional value creation, exploring the interdependencies among healthcare professionals, patients, managers, policymakers, technology providers, AI-based agents, and other relevant actors. The notion of hybrid intelligence is especially relevant in this context, as it emphasises the potential to combine complementary human and artificial capabilities rather than treating them as competing alternatives (Dellermann et al., 2019). Healthcare provides a particularly meaningful setting for studying these dynamics. Although digital technologies can improve healthcare quality, accessibility, efficiency, and coordination, outcomes depend on their integration with organisational practices, institutional arrangements, and patterns of use (Agarwal et al., 2010). Evidence from AI-supported medical diagnosis also shows that algorithmic opacity affects how professionals engage with AI-generated recommendations and exercise judgement in high-stakes decisions (Lebovitz et al., 2022). Consequently, introducing AI is not the same as implementing it: value emerges from the interaction between technological capabilities and the organisational practices, professional judgement, and routines through which they are enacted (Van Noordt & Tangi, 2023).

The track welcomes theoretical, empirical, methodological, and practice-oriented contributions from several research fields such as innovation management, knowledge management, co-creation, operations management, organisational studies, digital transformation, and performance assessment. The aim is to understand how the interaction between human and artificial intelligence can enhance learning, collaboration, innovation, and decision-making while preserving knowledge diversity, human judgement, trust, inclusion, and accountability on which the long-term vitality of the ecosystem depends. By connecting technological transformation with organisational, relational, and ethical dimensions, the track aims to advance understanding of how healthy, resilient, and value-generating healthcare knowledge ecosystems can be designed, governed, and evaluated as well as how their vitality can be assessed beyond conventional measures of efficiency.