Patients, families and even referring clinicians are now relying on AI systems, AI Overviews, LLMs, chatbots and navigation tools, as the de facto front door to health systems. When those systems hallucinate, rely on bad data or surface outdated information, hospitals pay the price in brand damage, clinical risk and operational friction.

This session introduces a practical framework to diagnose and fix what AI sees and says about your organization. You’ll learn how AI misrepresents health systems, how fragmented data and broken knowledge graphs undermine visibility, and how to build an “Everywhere” presence that positions your organization as a trusted, authoritative source in AI-driven search.

Learning objectives:

• Identify at least three ways AI systems can misrepresent or misroute patients to and from organizations and quantify the associated brand, safety and access risks.
• Design a basic knowledge graph cleanup and Everywhere stack plan that connects SEO, listings, reviews, PR and content so AI tools see their organization as a consistent, authoritative source.
• Implement an AI oversight playbook including monitoring, clinical, brand, legal review and correction workflows to continuously improve what AI says about their hospitals and key service lines.