In an era where patients and clinicians increasingly turn to artificial intelligence for medical advice, a critical question emerges: Does AI know when not to test or treat? A new joint study from Ben-Gurion University of the Negev (BGU) and Clalit Health Services reveals that leading large language models (LLMs) successfully identify when medical interventions are redundant in the vast majority of cases, stumbling primarily in gray areas where medical consensus itself is divided.