Abstract

ABSTRACT The adoption of artificial intelligence (AI) in healthcare offers significant potential for improving clinical performance and operational efficiency, yet implementation projects frequently encounter failure due to technical complexity, governance constraints, and organizational readiness challenges. This research-in-progress reframes healthcare AI adoption as an information systems project management problem rather than solely a technology adoption issue. Based on a systematic literature review of AI barriers and enablers, adoption barriers are conceptualized as project risks and adoption enablers as project success factors, extending PMBOK and ISO 31000 into the healthcare AI context. Preliminary findings identify governance, data quality, interoperability, and stakeholder readiness as dominant risk domains, while leadership support, agile methods, stakeholder engagement, and regulatory alignment emerge as key success factors.

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