Madan Moudgal is helping healthcare organizations use AI to improve operations without removing the human judgment that sensitive clinical decisions require. As Chief Digital Officer at Sagility, he leads technology transformation for a healthcare operations company serving U.S. payers and providers. Sagility’s Nurse Assist solution recently won an AI Excellence Award for helping clinical teams review prior authorization cases faster and more accurately.

In this episode, Russ and Madan explore why healthcare is one of the hardest industries to modernize with AI. Madan explains how legacy systems, strict regulation, data privacy requirements, and complex workflows make healthcare transformation different from other industries.

They dive into prior authorization, one of healthcare’s most difficult and controversial processes. Madan explains why the process exists, how it helps address waste, fraud, and abuse, and why the challenge is balancing cost control with patient access to appropriate care.

The conversation also covers why Sagility uses the term augmented intelligence instead of full automation. Madan explains that AI can summarize documents, extract relevant clinical details, compare information against guidelines, and provide recommendations, but nurses and clinical experts still need to make the final decision.

Along the way, Madan discusses domain-specific AI models, clinical language models, guardrails, PHI protection, data curation, AI governance, change management, and why successful healthcare AI requires careful testing, incremental rollout, and trust-building over time.

Topics Covered:

[00:00] Welcome and intro, Madan Moudgal and Sagility’s AI Excellence Award win

[00:32] Sagility’s background as a healthcare operations company

[01:21] Why healthcare and payment systems are so complex

[01:43] The challenge of adopting AI in a regulated healthcare environment

[02:37] Lessons from implementing technology change in healthcare

[02:47] Working around large legacy healthcare systems

[03:45] Why prior authorization is such a difficult healthcare problem

[03:57] Balancing waste reduction, cost control, and patient access to care

[05:27] Why Sagility uses augmented intelligence instead of automation

[05:40] Keeping humans in the loop for clinical decision-making

[06:46] Where AI can help and where humans must remain accountable

[09:14] Extracting and summarizing clinical data from case documents

[10:27] Why Sagility focuses on domain-specific AI models

[11:03] Building trust through clinical language models

[12:01] Why accuracy is essential in healthcare AI

[13:18] Guardrails for compliance, PHI, and regulatory requirements

[14:37] Reducing review time and what that means for patients

[15:35] Reviewing medical records, clinical guidelines, and recommendations

[16:34] How Nurse Assist supports nurse reviewers

[17:43] Early benefits from speed, efficiency, and lower costs

[18:38] Integrating AI with legacy healthcare systems

[18:56] Why data curation matters before AI can work effectively

[20:24] AI governance and aligning with client policies

[20:47] Change management in enterprise healthcare workflows

[21:50] Balancing innovation and risk management in healthcare

[22:42] Why healthcare AI rollouts cannot be rushed

[24:44] Whether healthcare will ever become fully automated

[25:06] Why healthcare is more likely to remain augmented than fully automated

[27:44] Other healthcare areas ready for AI transformation

[28:22] Automating simpler member and patient interactions

[29:27] Virtual agents and consumer expectations in healthcare

[30:50] Claims accuracy and payment integrity opportunities

[32:04] What healthcare may look like in the next 30 years