Toward human+ medical professionals: navigating AI integration in healthcare to enhance human expertise

Abstract

Purpose This study aims to analyse the different levels of human–AI interaction in healthcare and their impact on human expertise within innovation management practices. Specifically, the research seeks to investigate how the use of AI in healthcare transforms medical practitioners into Human + professionals, and what are the implications for innovation management practices. Design/methodology/approach This study employs a qualitative research design based on a multiple case study approach. Four AI applications in healthcare were selected and analysed to explore various configurations of AI–human interactions. Data analysis was guided by the three-dimensional conceptual framework proposed by Bolton et al. (2018), which provides a comprehensive lens for examining service innovation dynamics within AI-enabled healthcare systems. Findings Drawing on Bolton et al. (2018) framework, the research identifies three levels of AI interaction in healthcare, each linked to innovation categories, human expertise and impact on innovation management. Case studies illustrate varying AI integration levels: AI-assisted automates highly repetitive tasks, increasing service availability, AI-augmented supports real-time medical tasks and AI-automated streamlines processes while preserving human oversight. The analysis highlights how AI reshapes healthcare, emphasising the irreplaceable role of human expertise in innovation. Originality/value This study provides a theoretical lens for analysing and interpreting AI adoption in healthcare, highlighting the spectrum of AI roles, innovation categories and impacts. It offers a valuable framework for managing human–AI interactions while preserving human expertise in the evolutionary path toward Human+.

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