AI Governance in Healthcare: Legal and Policy Challenges in Regulating Clinical Decision Systems

Abstract

The integration of artificial intelligence (AI) in health care is revolutionizing diagnostic accuracy, therapy and efficiency. But the incorporation of AI poses important ethical, legal and regulatory considerations that need to be assessed. The purpose of this research is to examine the state of AI governance in healthcare, with a particular emphasis on ethical aspects, regulatory approaches and deployment challenges. We employed a narrative and comparative review approach, integrating evidence from recent research, policy and regulatory frameworks, and international guidelines. The analysis explores critical aspects such as privacy, bias, explainability, accountability, and safety, as well as current governance frameworks and global regulatory initiatives. The findings reveal that although AI holds significant promise for improving health outcomes, regulatory inconsistencies, explainability, and lower stakeholder trust pose barriers to its use. Additionally, variations in regional regulatory approaches pose implementation and interoperability challenges. The research recommends a holistic, interdisciplinary governance strategy including ethical considerations, effective regulation, and technological advancement to ensure the safe, equitable and trusted use of AI in healthcare. Researchers should prioritise the creation of standardised approaches to validating AI, improvements in explainable AI, and international cooperation to align regulatory approaches.