Medicine has always demanded proof before trust — not performance, but evidence of healing. As artificial intelligence enters clinical workflows with impressive benchmark scores but limited prospective validation, a familiar tension resurfaces: the gap between what a tool appears to do and what it actually does for patients. Researchers and regulators are calling for the same standard medicine has long required of drugs and devices — randomized controlled trials — before AI systems become embedded in the care of vulnerable people.
Medical AI Faces Proof Problem: Clinical Evidence Gap Widens
Potential patient harm from unvalidated medical AI systems deployed without adequate clinical evidence.