Build or Buy: A Practical AI & RPA Playbook for the Modern RCM Owner/Operator

3 Session Virtual Workshop
Tuesday April 21st 10am PT/11am MT/12pm CT/1pm ET
Thursday April 23rd 10am PT/11am MT/12pm CT/1pm ET
Tuesday April 28th 10am PT/11am MT/12pm CT/1pm ET

Members: $199
Non Members: $399
This program is scheduled for 3.5 hours over 3 days and is valid for 3.5 CHBME credits.

This immersive three-day workshop is led by Revenue Cycle Management (RCM) leadership from the HBMA and Innovations Committee with real world experience in implementing AI and Robotic Process Automation (RPA) in real operating environments—not just in theory. The course is designed for RCM leaders who want to leverage automation and AI to drive margin, scalability, and defensibility without over leveraging themselves.

Participants will learn how to identify high-value automation opportunities across the RCM lifecycle, evaluate AI and RPA solutions through a true ROI lens, and make disciplined build-vs-buy decisions that align with their company’s size, growth goals, and risk tolerance. The workshop blends strategic frameworks with hands-on evaluation methods, real-world case studies, and decision tools that attendees can immediately apply inside their own organizations.

Day 1 - April 21st

Develop a Repeatable Build-vs-Buy Decision Framework (60 Minutes)
Learn how to objectively evaluate whether an AI or RPA solution should be built internally or purchased, using criteria such as strategic differentiation, total cost of ownership, implementation risk, scalability, and long-term competitive advantage.

Day 2 - April 23rd

Identify High-ROI AI & RPA Use Cases in RCM Operations (90 Minutes)
Gain clarity on which RCM workflows (e.g., eligibility, authorizations, coding support, payment posting, denial management, analytics) deliver meaningful returns when automated—and which are better served by process or vendor optimization instead of custom development.

Day 3 - April 28th

Translate Technology Decisions Into Measurable Business Value (60 Minutes)
Understand how to quantify value beyond “efficiency,” including margin expansion, labor leverage, error reduction, client retention, pricing power, and enterprise value—so AI and RPA investments are tied directly to business outcomes, not just technical capabilities.