As payers increasingly deploy AI and automation to accelerate denials and reduce payments, health systems must evolve their own technology strategies to keep pace. This session will share best practices for integrating AI, automation, and machine learning into revenue cycle operations—drawing on real-world examples from leading health systems, hospitals and practices.  Explore the journey of implementing automation and machine learning while navigating governance, overcoming technical hurdles, and fostering adaptability across teams.

Learning Objectives:

• Understand technical and operational obstacles in adopting automation and AI tools, and learn proven strategies to overcome them effectively.
• Gain insights into building flexible governance frameworks, supporting staff education, and fostering adaptability to maximize the impact of emerging technologies in your revenue cycle.

As AI use rapidly expands across health plan operations, understanding how these technologies will be governed is essential. In this session, experts will take a deeper dive into the current state of AI governance frameworks and the legislative landscape shaping their use. Health plan leaders will gain timely insights into what’s happening now—and what’s coming next—in AI oversight, helping them prepare their organizations for compliance, accountability, and responsible innovation.

Learning Objectives: 

• Learn how to assess, document, and monitor AI models used in claims review, fraud detection, and payment integrity to ensure they meet accountability, explainability, and compliance standards.
• Gain actionable insights into current and pending legislation on AI use in healthcare, and understand what steps your organization should take now to align with evolving regulatory expectations and avoid audit risks.