From Ethical Review to Governance Oversight: A PMI-CPMAI Model for Healthcare AI Projects and Programs

Abstract

This article examines how AI ethics committees can be integrated into healthcare project governance using a PMI-CPMAI aligned oversight model. In this study, ethics refers to the governance of fairness, transparency, accountability, patient safety, and responsible decision-making in healthcare AI systems.The topic matters because healthcare organisations are increasingly using AI in areas such as risk prediction, monitoring, scheduling, and clinical decision support, yet ethical oversight often remains weak, late, or unclear. The study used a qualitative approach and drew on four semi-structured interview responses collected from healthcare professionals in management and clinical roles. The findings show an uneven picture. Some respondents reported the presence of an ethics committee, while others did not. Even where some form of oversight existed, authority was often advisory, escalation routes were weak, and monitoring after deployment was inconsistent. Respondents also pointed to practical obstacles such as the absence of clear policy, limited AI understanding among reviewers, and low involvement of frontline staff. The article argues that healthcare organisations need more than broad ethical awareness. They need a clearer governance arrangement that places ethical review inside project stages, decision gates, accountability structures, and post-deployment follow-up. A PMI-CPMAI aligned oversight model offers a practical route for doing this by placing governance, validation, and lifecycle control within the management of AI initiatives rather than treating ethics as a separate compliance exercise (Project Management Institute, 2023).