Regulating the Unseen: AI Accountability in UK Healthcare Sector

Abstract

The integration of Artificial Intelligence (AI) into healthcare reveals persistent accountability gaps shaped by system opacity, adaptive model behaviour and distributed responsibility across the clinical and technological ecosystem. As accountability becomes a central principle of AI governance, this article develops a conceptual framework and applies it to the UK’s hybrid regulatory landscape. Using the four-layer model advanced by Novelli, Taddeo, and Floridi (2024) – comprising compliance, report, oversight and enforcement – the article examines how accountability is operationalised within UK healthcare through medical device regulation, digital safety standards, transparency mechanisms and post-market monitoring. The analysis shows that although the UK has a broad assemblage of regulatory and governance tools, their fragmentation generates interconnected accountability gaps, including deficiencies in evidence generation, transparency, attribution and institutional learning. The article argues that closing these gaps requires greater interoperability between governance layers, clearer allocation of responsibilities across developers and deployers, strengthened institutional capability and more effective regulatory coordination. It therefore proposes a multi-layered governance model in which the four accountability layers operate through continuous feedback loops, enabling a lifecycle-oriented approach to the responsible development and deployment of AI in the UK healthcare system.