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Making Artificial Intelligence Sustainable for Healthcare

Par : Contributeur(s) : Type de matériel : TexteTexteLangue : français Détails de publication : 2024. Sujet(s) : Ressources en ligne : Abrégé : This research aims to define a roadmap for the sustainable implementation of Artificial Intelligence (AI) in healthcare. Based on Triple Bottom Line (TBL) and the theory of dynamic capabilities (DC), the study highlights which steps and capabilities are needed to ensure an Artificial Intelligence (AI) implementation guaranteeing the three levels of sustainability (people, profit and planet). This study tries to respond to the following research question: How can healthcare organizations ensure sustainable implementation of Artificial Intelligence? An exploratory qualitative analysis was conducted using the focus group method. The results highlight six main steps for the sustainable implementation of AI, each with specific capabilities to be developed. This study provides implications for both theory and practice. Future research will be needed to investigate the emerging aspects. JEL CODES: M21, I15, O30
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This research aims to define a roadmap for the sustainable implementation of Artificial Intelligence (AI) in healthcare. Based on Triple Bottom Line (TBL) and the theory of dynamic capabilities (DC), the study highlights which steps and capabilities are needed to ensure an Artificial Intelligence (AI) implementation guaranteeing the three levels of sustainability (people, profit and planet). This study tries to respond to the following research question: How can healthcare organizations ensure sustainable implementation of Artificial Intelligence? An exploratory qualitative analysis was conducted using the focus group method. The results highlight six main steps for the sustainable implementation of AI, each with specific capabilities to be developed. This study provides implications for both theory and practice. Future research will be needed to investigate the emerging aspects. JEL CODES: M21, I15, O30

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