# AI vs. AI: The Next Generation of Revenue Cycle Management — A Conversation with ModMed's Rob Ware

Page: https://stenobird.com/podcast/mgma-podcasts-220052/ai-vs-ai-the-next-generation-of-revenue-cycle-management-a-conversation-with-modmed-s-rob-ware
Text version: https://stenobird.com/podcast/mgma-podcasts-220052/ai-vs-ai-the-next-generation-of-revenue-cycle-management-a-conversation-with-modmed-s-rob-ware.md
Podcast: [MGMA Podcasts](https://stenobird.com/podcast/mgma-podcasts-220052)
Published: 2026-08-26T11:00:00+00:00
Episode link: https://mgma-podcasts.transistor.fm/780
Audio file: https://media.transistor.fm/c645fda4/a046cf78.mp3
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JSON: https://stenobird.com/v1/public/podcasts/mgma-podcasts-220052/episodes/ai-vs-ai-the-next-generation-of-revenue-cycle-management-a-conversation-with-modmed-s-rob-ware
Duration seconds: 1624

## Resource

On this episode of the MGMA Insights Podcast , host and senior editor Daniel Williams has a conversation with Rob Ware, senior vice president and general manager of revenue cycle management at ModMed, about how artificial intelligence is reshaping medical billing and financial operations. Ware explains why revenue cycle management has reached an inflection point, how organizations can respond as payers adopt increasingly sophisticated technology, and what practice leaders should examine before adding another solution to their technology stack. Episode takeaways Revenue cycle management is moving beyond rules and individual expertise. Billing has traditionally depended on experienced professionals navigating an enormous and constantly changing mix of payers, plans, codes and requirements. Machine learning and AI can evaluate more of those variables at once, giving organizations an opportunity to make revenue cycle performance more consistent and scalable. Smaller amounts of revenue can no longer be dismissed. Rising operating costs, stagnant reimbursement and expanding administrative requirements have narrowed practice margins. Under those conditions, improving net collection rate by even one or two percentage points can have a meaningful financial impact. Practices increasingly need to “fight AI with AI.” Payers are using automation and AI to apply edits, conduct initial claim reviews and accelerate denial decisions. Practices need tools capable of identifying changing denial patterns quickly, rather than relying exclusively on monthly or quarterly reports that describe problems after they have already affected cash flow. Technology purchases should begin with a specific source of pain. Before selecting a solution, leaders should determine whether their primary leakage…

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