In this episode, Aditya Bansod, CTO and Co-Founder of Luma Health, about why healthcare AI often underdelivers — and what leaders must do to turn promise into performance.

Aditya argues that AI’s challenge in healthcare isn’t ambition, but execution. While new tools are emerging rapidly, most remain point solutions that fail to integrate into the complex workflows that move patients from scheduling to care delivery. True impact, he says, depends on orchestrating the “last mile” of healthcare, referrals, intake, documentation, and the countless operational handoffs that determine whether care actually happens.

He shares how Luma approaches AI adoption with flexible guardrails, allowing health systems to calibrate automation based on confidence thresholds and maturity. The conversation also explores the rise of agentic AI, the tension between human-in-the-loop oversight and autonomy, and why CIOs are navigating a messy but necessary consolidation phase.

Looking ahead, Aditya is optimistic that AI will transform patient access and engagement, only if it’s deeply embedded into workflows, not layered on top of them. Take a listen.



In this episode, Dr. Andrea Willis, SVP and Chief Medical Officer at BlueCross BlueShield of Tennessee, shares how payers can harness AI to advance affordable, accessible, and more human-centered care.

From her clinical roots to leading population health, quality, and health equity initiatives, Dr. Willis brings a deeply personal commitment to service. She describes how AI is being deployed across care management and utilization management, not to replace clinicians or deny care, but to augment teams, accelerate evidence-based decisions, and close gaps in care. In care management, AI-powered summarization and prompting help staff stay fully present with members while improving engagement and measurable outcomes. In utilization management, transparency, evidence-based criteria, and clear documentation remain foundational to rebuilding provider trust. She also highlights that relevance matters more than data volume, and that guided self-service must balance automation with timely human escalation.

Dr. Willis emphasizes transparency in prior authorization, cross-functional governance, AI literacy goals across the enterprise, and strong PHI protections. For here, scaling AI responsibly – through interoperability, collaboration, and measurable impact – is key to rebuilding trust and transforming the healthcare experience. Take a listen.

In this episode, Dr. Amit Phull discusses what responsible AI adoption in healthcare really looks like, starting with trust, usability, and preserving clinician judgment. He emphasizes that ease of use and confidence in outputs are non-negotiable for clinician adoption, especially in already time-constrained workflows.

The discussion also explores why AI must be built with clinicians, not simply deployed for them, and how poorly integrated tools risk adding friction instead of value. Dr. Phull also talks about preserving a clinician’s “spidey sense”—the intuition developed through experience—while using AI to augment, not override, clinical judgment. The conversation also touches on how success should be measured beyond dashboards, including recurrent use, time savings, and reductions in burnout.

Dr. Phull states that AI, when designed thoughtfully, can help clinicians reclaim time, sharpen expertise, and focus more fully on patient care, without losing the human edge that defines great medicine. Take a listen.