Denials are often blamed on payers or staffing shortages, but the true root causes usually begin much earlier in the workflow. This segment explores how diagnosing denials correctly allows AI to move from reactive appeals to proactive prevention and measurable financial improvement.

In this episode, Natalia Arzeno-Gonzalez, Chief Data Scientist at Infinx, helps revenue cycle leaders cut through the noise by setting realistic expectations for AI in RCM. The discussion explores what AI does well today, where it falls short, and why data readiness, workflow maturity, and integration matter more than buzzwords.

Brought to you by www.infinx.com

Even high-performing hospitals leave revenue on the table due to complexity, outdated charging methodologies, and process blind spots. In this episode, Anthony Amaya explains how disciplined charge capture optimization can deliver a measurable one to four percent net revenue lift without adding volume or increasing costs.

As AI becomes embedded into revenue cycle workflows, accountability can no longer be treated as a black box owned by technology. This episode explores how leaders should set expectations, measure outcomes, and stay responsible for results even as automation scales.

This episode, recorded live from the Oregon HFMA Winter Conference, reflects on how change shows up across healthcare revenue cycle operations and how augmented intelligence has become a recurring thread connecting those experiences. We’ll explore why some parts of healthcare evolve quickly while others resist change, and what that means for the people navigating it every day.

Brought to you by www.infinx.com

In this episode of Revenue Cycle Optimized, Jennifer Glockzin, Senior Director of Patient Access at Infinx, walks through the real-world prior authorization process from intake to determination and appeals. Her breakdown highlights how disciplined workflows, supported by AI agent automation and coordinated human in-the-loop, protect revenue and reduce preventable denials.

When leaders ask “Why AI?” in revenue cycle, they’re often reacting to growing complexity, staffing pressure, and loss of control rather than chasing innovation. This segment reframes the AI conversation around stability, predictability, and restoring confidence in day-to-day operations.

In this episode, Jaideep Tandon, CEO of Infinx, shares a sensible, leadership-driven perspective on the evolving role of AI in RCM. Rather than focusing on technology for technology’s sake, the conversation centers on outcomes: improving efficiency, reducing revenue leakage, and supporting better financial decision-making across increasingly complex healthcare environments. Jaideep addresses how revenue cycle leaders can play a more active role in shaping AI success with a clearer understanding of how to evaluate AI initiatives, set realistic expectations, and lead AI adoption as an ongoing journey.

Brought to you by www.infinx.com

In this segment from What’s My Tagline? with host Carol Flagg, Stuart Newsome discusses why AI messaging in healthcare is hitting a wall and how skepticism is forcing a shift toward outcomes-based positioning. The conversation explores what revenue cycle leaders actually care about in 2026 — trust, specificity, governance, and real operational impact.

AI agents create the most value in revenue cycle workflows when they operate as a coordinated system rather than isolated tools. This episode explores how multi-agent orchestration combined with a tech-enabled human layer delivers reliability, accountability, and real operational outcomes in RCM.