Healthcare has spent three years building AI governance on paper: committees chartered, policies approved, vendor contracts updated. Clearwater’s new industry benchmark asked a harder question: can organizations actually prove any of it works? The answer, drawn from responses across hospitals, health systems, physician groups, health plans, and healthcare technology companies, revealed a widening gap between what’s documented and what’s technically verified.
In this webinar, Harry Lu, Clearwater’s Vice President of AI Solutions, walked through the report’s five key findings, including why only 8.6% of organizations can verify their AI inventory through automated discovery, why third party AI is the most feared and least validated risk in the ecosystem, and why agentic AI is already operating in production faster than the controls meant to govern it.
In this session, attendees learned:
- The gaps separating stated AI governance from technical assurance across inventory, data, vendors, frameworks, and funding
- Why policy based controls are no longer enough for AI running at production scale
- The questions every organization should be able to answer about any AI agent operating in its environment
- Where accreditation bodies and clients are already raising the bar from “do you have a policy” to “can you prove it works”
- Practical first steps to move from describing controls to demonstrating them
Whether you’re building an AI governance program from scratch or trying to determine whether your existing one can survive scrutiny, this on demand session gives you a clear, evidence driven picture of where the industry stands and where your organization stands against it.
