AI Doctors Face a New Test: The Benchmarking Problem

Comparing artificial intelligence tools designed for doctors is becoming a difficult task. A recent analysis of clinical chatbots from companies like OpenEvidence and Doximity highlights the complexity of measuring their performance. These AI systems, known as clinical large language models (LLMs), can answer medical questions and help with patient records. But experts warn that standard tests may not capture how well they work in real hospital settings. The challenge lies in creating benchmarks that are both fair and meaningful. Investors are also watching closely. The biopharma sector sees promise in AI, but questions remain about which models truly improve patient care. Without reliable comparisons, hospitals and doctors risk choosing the wrong tool. The conversation around these issues is just beginning. As AI moves further into medicine, the need for clear, unbiased testing will only grow.