Revenue Cycle Optimized

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.

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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.

EMR upgrades, clearinghouse changes, and AI are reshaping revenue cycle operations, but they can also disrupt cash flow if not carefully managed. This episode focuses on maintaining revenue continuity during system transitions, highlighting where delays commonly occur, how AI fits into modern workflows, and what operational safeguards help ensure revenue continues to flow through change.

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In this episode, Navaneeth Nair, Chief Product Officer at Infinx, explains what it really takes to make AI work in revenue cycle management, from decomposing workflows into task-level agents to maintaining human-in-the-loop oversight. The conversation explores why effective RCM automation depends on orchestration, agent lifecycle management, and tech-enabled workflows designed for real operational complexity.

In this RCMinutes episode of the Revenue Cycle Optimized podcast, we unpack what healthcare teams truly trust about AI, and what still makes them hesitate. Drawing from real conversations with providers, this episode explores why reliability, transparency, and workflow alignment matter more than flashy automation.

AI can extract data from documents—but making that data usable, reliable, and scalable is where most efforts fall apart. In this episode, Charu Nevatia explores why AI document capture isn’t plug and play and what it really takes to operationalize it in healthcare.

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Ambulatory and acute care billing share many of the same building blocks, but the way data, workflows, and reimbursement are structured creates very different operational realities. In this episode, we explore how those differences shape not only revenue cycle strategy, but also how automation and AI should be applied effectively with these considerations across care settings.

Healthcare’s cautious approach to AI isn’t resistance to innovation, it’s a response to real operational, clinical, and financial risk. In this episode, we unpack why moving slowly is often the smartest move, and how intentional adoption builds trust, safety, and long-term value.

As payors increasingly use AI to review documentation and accelerate denials, radiology practices must adapt. This session explores how stronger documentation, AI-supported workflows, and proactive compliance strategies can reduce preventable denials and protect revenue in an evolving payer landscape.

Brought to you by www.infinx.com