Artificial intelligence isn’t failing radiology. Our healthcareinfrastructure just isn’t ready for it.

In this episode of Contrast & Clarity with the JACR, we cut through the hype to tackle the real reason artificial intelligence hasn’t transformed radiology yet—and it’s not because the algorithms aren’t good enough.

Joined by Michael Bruno, MD, MS and drawing from insightshighlighted at the 2024 Intersociety Summer Conference, Maddi and Jeff unpack the systemic barriers holding AI back: legacy IT systems, fragmented data pipelines, regulatory uncertainty, and workflows that force humans and AI to coexist rather than collaborate.

We discuss:

• Why AI keeps getting treated as a “bolt-on” instead of afoundational tool

• The mismatch between AI’s potential and real-world clinicalworkflows

• Why ROI, governance, and trust—not accuracy—are stalling adoption

• What actually needs to change for AI to move from demo todeployment

This isn’t a conversation about shiny tools or futuristic promises.

It’s about systems, incentives, and the uncomfortable reality that AI won’t fix radiology until we fix the environment it’s deployed into.

If you’ve ever wondered why AI feels simultaneously inevitable and underwhelming—this episode is for you.

Find the JACR article here: https://www.jacr.org/article/S1546-1440(25)00444-2/abstract

Claim your CME credit here: https://shorturl.at/u6Hcj

32. AI Roadblocks Part 1: The Infrastructure Problem *CME*

32. AI Roadblocks Part 1: The Infrastructure Problem CME