The mid-revenue cycle has long been one of healthcare's most complex and most
overlooked sources of financial leakage, clinical burden, and operational risk. Utilization
management, concurrent authorization, and care coordination remain largely manual,
siloed, and inconsistent, costing health systems millions in avoidable denials, rework,
and lost revenue. Meanwhile, clinical staff are spending critical time on administrative
tasks rather than on patient care, accelerating burnout and straining an already
stretched workforce.

The question is no longer whether AI can help. The question is: how do you implement
AI responsibly, at scale, and in a way that earns the trust of your clinical, financial, and
IT stakeholders?
 

Join healthcare leaders in this session for a cross-functional perspective on what it
takes to modernize the mid-revenue cycle with advanced intelligence. Drawing on real-
world health system experience, speakers will explore the operational, clinical, financial,
and governance aspects of AI-powered UM transformation and what leaders across the
enterprise need to understand to drive outcomes.

By the end of this session, attendees will be able to:

• Articulate the true financial and operational cost of mid-revenue cycle inefficiency and how to build a case for modernization leveraging AI
• Apply a strategic framework for aligning clinical, IT, finance, and revenue cycle teams around shared KPIs and measurable outcomes.
• Understand how intelligent automation can simultaneously improve denial prevention, strengthen payer relationships, optimize human capital, and drive sustainable margin improvement.