Reconfiguring business model dimensions for value creation: AI adoption in health care

Purpose The rapid proliferation of artificial intelligence (AI) applications in health care has gained significant attention due to their transformative potential. Given the heterogeneity of actors developing and offering AI solutions in health care, this study aims to address the reconfiguration of business models for AI adoption and value creation. Design/methodology/approach Through qualitative research, data were extracted and analyzed from 23 semistructured interviews with health-care professionals, AI and machine learning technology developers and business professionals. Findings It highlighted the business model reconfiguration across the value structure, offer system and demand system for AI adoption. Research limitations/implications This research focuses on data-driven and image-based AI applications in health care rather than on AI’s potential in operational areas such as process design, supply chain management and scheduling. Practical implications This research offers a more detailed understanding of the business model reconfiguration for AI applications in health care, going beyond technical and medical considerations. Social implications This research emphasizes the need for unbiased data, patient privacy and cybersecurity in AI health-care systems. Originality/value This research addresses AI adoption in health care from a business model perspective rather than from technical or clinical perspectives.