AI Chatbots Miss Eight in Ten Early Diagnoses. Hospitals Are Still Buying In.

The JAMA study's core finding reframes the AI diagnostics conversation in a way that performance leaderboards cannot absorb: the failure is structural, not marginal. When patient information is complete, frontier models perform well — some exceed 90% final-diagnosis accuracy. But complete patient data is a condition that describes late-stage clinical encounters, not the triage moment when a decision about urgency actually matters. Every model tested failed that earlier, harder task more than 80% of the time ^[1].