As AI tools become embedded in clinical workflows—from note drafting to radiology reads—early evidence suggests that over-reliance may erode clinical skills, a phenomenon known as de-skilling.
A 2025 study in The Lancet Gastroenterology & Hepatology found that endoscopists who routinely used AI-assisted adenoma detection experienced a decline in detection rates (29% to 22%) when AI was removed. The finding suggests sustained AI exposure may weaken independent diagnostic performance.
Cognitive psychology research points to cognitive off-loading as a likely mechanism: when clinicians passively accept AI outputs, analytic reasoning declines. This risk appears especially pronounced among less experienced clinicians. Studies in radiology show that junior radiologists are far less likely than senior colleagues to detect AI errors—raising concerns about “never-skilling,” where trainees fail to fully develop diagnostic mastery in the first place.
