Healthcare AI Governance, Risk, and Compliance (GRC)
Open Until: 08/01/2026
It is becoming increasingly common for Healthcare Organizations to use Artificial Intelligence (AI) services, but the transition to AI presents challenges. One of the main challenges is establishing Governance, Risk, and Compliance (GRC), which requires redefining business and technology processes and relying on third-party providers. To ensure that healthcare organizations can reap the benefits of AI, it is essential to design and implement a robust GRC program that addresses these challenges and ensures compliance with regulations and standards. Effective AI governance requires a holistic approach, from understanding your organization’s use of AI, the data involved, the business units operating AI systems, the management chain of responsibility, and ultimately the board. This paper will show how to address healthcare AI GRC.
Key Takeaways
- Healthcare organizations need robust AI GRC frameworks to manage AI-specific risks including bias, model drift, and privacy violations. NIST AI RMF and ISO/IEC 23894 provide structured risk management approaches. Compliance spans HIPAA, FDA SaMD requirements, and the EU AI Act. CSA's AICM and CCM offer vendor-agnostic control frameworks. Auditing must address four domains: bias detection, explainability, performance/drift monitoring, and regulatory compliance. Privacy-by-design and PETs (homomorphic encryption, TEEs, differential privacy) are essential for PHI protection. An agile GRC approach is required given rapidly evolving AI regulation.
