AI is no longer a future concept in revenue cycle management—it is already embedded across workflows, platforms, and decision-making processes. Yet many healthcare organizations are discovering that adoption alone does not guarantee impact. As expectations rise, so does the need for clarity around what AI should realistically deliver and how leaders should guide its use.
In this Office Hours session, Jaideep Tandon, CEO of Infinx, shares a pragmatic, 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 discusses why fragmented data, payer variability, and operational nuance make oversimplified AI narratives risky—and how leaders can avoid these traps.
The session also addresses how revenue cycle leaders can play a more active role in shaping AI success by bringing their institutional knowledge into technology conversations, prioritizing proof-of-concept approaches, and embracing incremental gains over perfection. Attendees will leave with a clearer understanding of how to evaluate AI initiatives, set realistic expectations, and lead AI adoption as an ongoing journey rather than a one-time implementation.
Learning Objectives
- Understand how AI in revenue cycle management is evolving from hype-driven experimentation to outcome-driven accountability.
- Identify common misconceptions and risks that prevent AI initiatives from delivering measurable ROI in complex healthcare environments.
- Apply a leadership-focused framework for evaluating, piloting, and scaling AI initiatives that balance innovation with operational reality.
Request a demo of our revenue solutions to learn more.