Computer-aided detection in colonoscopy has an unusually strong evidence base by clinical AI standards, with multiple randomized trials showing improved adenoma detection. A large multi-site trial reporting this month found no overall effect, and the authors' analysis of why is more useful than the headline.

Detection improved substantially among endoscopists in the lowest quartile of baseline performance and not at all among those in the highest. Since the participating sites in this trial were disproportionately high-volume centers with strong baseline detection rates, the pooled effect washed out.

This is a ceiling effect and it is not surprising, but it has a direct implication for deployment: the tool's value is concentrated where baseline performance is weakest, which is generally not where these tools are purchased first.

The authors argue for a targeted deployment strategy and for reporting baseline-stratified results in all future trials. They also note, in a line worth flagging, that identifying which endoscopists would benefit requires measuring individual performance — an intervention that some sites may find more difficult to implement than the software.