Rethinking national health innovation systems for AI: Emphasizing trust building and user-integration

Abstract

The growing importance of artificial intelligence (AI) in healthcare underscores the need for a systematic understanding of the innovation processes within national health innovation systems (NHIS). Innovation activities in this domain take place within complex systems shaped by technological, organizational, regulatory, societal, and ethical challenges, necessitating a comprehensive framework to address the interdependencies between actors and institutions. An innovation system (IS) perspective provides a robust approach to analyse these complexities. This study employs a case study approach, drawing on data from 32 semi-structured interviews and multiple other sources, to investigate the structural and dynamic components of NHIS for AI in Germany and Sweden. Our findings suggest that established IS functions, such as knowledge development and diffusion, entrepreneurial experimentation, or market formation, are only partially fulfilled in the context of healthcare AI. The analysis indicates the need to adapt IS frameworks to address the specific challenges posed by AI, particularly in healthcare. Our study proposes “trust building” as a central function of NHIS, alongside presenting the dimensions of user-integration and societal impact for IS theory. These findings contribute to advancing IS and AI research and provide a foundation for studying the effective and responsible integration of AI into healthcare systems. • Adaptation of innovation system frameworks to AI challenges and opportunities • National health innovation systems for AI of Germany and Sweden • Introduction of “trust building” as a central function of innovation systems • Integration of user-integration and societal impact into innovation systems

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