AI and Healthcare

AI is transforming healthcare at an unprecedented pace—but the biggest risks aren’t clinical, they’re legal, operational, and systemic. From data center infrastructure and environmental impact to reimbursement shifts and agentic AI workflows, the stakes are rising fast. New models from major tech players are poised to influence care delivery—and even get reimbursed based on outcomes—raising critical questions about ownership, liability, and control. Where does responsibility fall when AI drives decisions? How should hospitals evaluate vendors, data sources, and infrastructure risks? And what happens when automation outpaces regulation?

AI is making remarkable progress in healthcare — but translating that progress into real clinical impact is more complex than it seems. In this episode, we break down the State of Clinical AI in 2026, separating signal from noise and exploring what’s actually working today.

AI is exploding in healthcare — but most startups still fail. In this episode of the AI & Healthcare Podcast, Dr. Sanjay Juneja speaks with innovation leaders Dr. Bernardo Perez-Villa and Dr. Peter Alperin about the reality of building successful medical technology in 2026. Hundreds of AI tools have FDA clearance, billions have been invested in digital health, and yet hospitals still struggle to adopt new technology. Why?

Care is delivered every day in American hospitals, but getting paid for that care has become a battle. Denials, prior authorization, billing complexity, and rising costs have created a financial crisis behind the scenes of modern medicine. Insurance companies use automation to control payments, while hospitals struggle to keep up. Now AI is entering the fight. Dr. Sanjay Juneja and Dr. Douglas Flora speak with Monique Lappas, Founder and CEO of Qualify Health, about the growing war over who pays for care and how intelligent automation is helping providers recover lost revenue, reduce patient debt, and keep hospitals from closing.

Mental health is now central to high-quality cancer care, yet access, diagnostic precision, and scalability remain major gaps. In this in-depth discussion, clinical and innovation leaders explore how artificial intelligence can shift mental health care from reactive support to precision-driven, proactive intervention. The conversation examines AI as a clinical signal amplifier that enhances human judgment without replacing it. Topics include objective diagnostics, functional brain mapping, digital phenotyping, therapeutic bots, longitudinal monitoring, and how AI can better match patients to the right level of care at the right time. The discussion also addresses real-world implementation challenges in oncology and health systems, including workforce shortages, equity, and clinical oversight.