Regulatory Framework of Generative-AI in Healthcare: Insights from a Scoping Review

The integration of generative artificial intelligence (GenAI) in healthcare offers transformative opportunities. At the same time, it introduces significant regulatory challenges. GenAI systems like Google’s Med-PaLM and OpenAI’s GPT-4 hold promise for medical data synthesis, diagnostic support, and patient interaction. However, these advancements reveal significant gaps in existing regulatory frameworks. Critical issues include data privacy, safety, transparency, and accountability. This scoping review examines the fragmented regulatory environment for GenAI in healthcare. It highlights ethical, legal, and operational complexities associated with these systems. The dynamic nature of GenAI, data security risks, algorithmic bias, and lack of explainability demand adaptive regulatory solutions. The study uses institutional theory to explore how healthcare organizations address regulatory pressures and align AI practices with societal and legal expectations. The findings underline the urgent need for comprehensive regulatory frameworks. These frameworks should balance innovation with patient safety and public trust. Transparency, ongoing monitoring, and international collaboration are highlighted as critical components. This review provides theoretical insights and practical guidance for regulators, healthcare providers, and AI developers. It outlines a pathway for the responsible and ethical integration of GenAI into healthcare.