How do radiologists keep an eye on the AI they use?
Interviews with 16 radiologists show that checking AI tools in practice is mostly manual, slow and unsupported by clear guidelines.
The question
As AI tools spread through radiology, it matters that someone keeps checking they still work well. Few people have asked how that checking is done today.
What we did
We interviewed 16 radiologists across Europe and the United States about how they monitor the AI tools they use and what gets in the way, and analysed what they told us.
What we found
Many AI systems are still at an early validation stage. Monitoring is usually manual, with radiologists comparing the AI output with radiology reports after the fact. That works but takes a lot of effort. The main barriers are a lack of standard guidance, limited technical tools and limited resources.
Why it matters
We recommend combining several monitoring methods, setting up dedicated governance teams, and planning resources for the long term. Clearer frameworks and investment are needed so that AI actually improves clinical workflows.