What really happens when a “smart” system steps into the operating room, and collides with the messy, time-pressured reality of clinical care?

In this episode, we unpack a multi-center pilot that streamed audio and video from live surgeries to fuel safety checklists, flag cases for review, and promise rapid, actionable insight. What emerged instead was a clear-eyed lesson in the gap between aspiration and execution. Across four fault lines, the story shows where clinicians’ expectations of AI ran ahead of what today’s systems can reliably deliver, and what that means for patient safety.

We begin with the promise. Surgeons and care teams envisioned near-instant post-case summaries: what went well, what raised concern, and which patients might be at risk. The reality looked different. Training demands, configuration work, and brittle workflows made it clear that AI is anything but plug-and-play. We explore why polished language can be mistaken for intelligence, why models need the right tools to reason effectively, and why moving AI from one hospital to another is closer to a redesign than a simple deployment.

Then we follow the data. When it takes six to eight weeks to turn raw footage into usable insight, the value of learning forums like morbidity and mortality conferences quickly erodes. Privacy protections, de-identification, and quality control matter—but without pipelines built for speed and trust, insights arrive too late to change practice. We contrast where the system delivered real value, such as checklists and procedural signals, with where it fell short: predicting post-operative complications and producing research-ready datasets.

Throughout the conversation, we argue for a minimum clinically viable product: tightly scoped use cases, early and deep involvement from surgeons and nurses, and data flows that respect governance without stalling learning. AI can strengthen patient safety and team performance—but only when expectations align with capability and operations are designed for real clinical tempo.

If this resonates, follow the show, share it with a colleague, and leave a review with one takeaway you’d apply in your own clinical setting.

Reference:

Expectations vs Reality of an Intraoperative Artificial Intelligence Intervention
Melissa Thornton et al.
JAMA Surgery (2026)

Credits:

Theme music: Nowhere Land, Kevin MacLeod (incompetech.com)
Licensed under Creative Commons: By Attribution 4.0
https://creativecommons.org/licenses/by/4.0/