ON DEMAND WEBINAR
Duration: 1 hour​

AI is rapidly evolving, but in healthcare the biggest barrier isn’t technology—it’s trust. This session breaks down why many AI initiatives underperform today and what it truly takes to make AI reliable, safe, and scalable across clinical and operational workflows. Through real-world examples, we’ll show how data quality and context directly shape AI outcomes and outline the foundational steps organizations need to build AI that clinicians and leaders can confidently rely on. You’ll learn:

• Why AI often fails in healthcare—and why the issues rarely come from the model itself
• How poor data erodes trust and leads to incorrect or risky outputs
• What “trusted AI” requires, from a strong semantic foundation to normalized, context-rich data
• Where to build vs. where to partner to achieve scale, sustainability, and readiness
• How to create an enterprise foundation that supports clinical, operational, and analytical AI use cases

SPEAKERS

Tim Yeager
Head of Product
Wolters Kluwer, Health Language

Brian Laberge
Solution Engineer
Wolters Kluwer, Health Language