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Organizational readiness for artificial intelligence in health care: insights for decision-making and practice
Organizational readiness for artificial intelligence in health care: insights for decision-making and practice
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Organizational readiness for artificial intelligence in health care: insights for decision-making and practice
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Organizational readiness for artificial intelligence in health care: insights for decision-making and practice
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Organizational readiness for artificial intelligence in health care: insights for decision-making and practice
Organizational readiness for artificial intelligence in health care: insights for decision-making and practice
Journal Article

Organizational readiness for artificial intelligence in health care: insights for decision-making and practice

2021
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Overview
PurposeArtificial intelligence (AI) raises many expectations regarding its ability to profoundly transform health care delivery. There is an abundant literature on the technical performance of AI applications in many clinical fields (e.g. radiology, ophthalmology). This article aims to bring forward the importance of studying organizational readiness to integrate AI into health care delivery.Design/methodology/approachThe reflection is based on our experience in digital health technologies, diffusion of innovations and healthcare organizations and systems. It provides insights into why and how organizational readiness should be carefully considered.FindingsAs an important step to ensure successful integration of AI and avoid unnecessary investments and costly failures, better consideration should be given to: (1) Needs and added-value assessment; (2) Workplace readiness: stakeholder acceptance and engagement; (3) Technology-organization alignment assessment and (4) Business plan: financing and investments. In summary, decision-makers and technology promoters should better address the complexity of AI and understand the systemic challenges raised by its implementation in healthcare organizations and systems.Originality/valueFew studies have focused on the organizational issues raised by the integration of AI into clinical routine. The current context is marked by a perplexing gap between the willingness of decision-makers and technology promoters to capitalize on AI applications to improve health care delivery and the reality on the ground, where it is difficult to initiate the changes needed to realize their full benefits while avoiding their negative impacts.