Healthcare AI agents: why evaluation must move from answers to actions

Healthcare AI is moving from answers to actions.

Stanford University's new MedAgentBench tests AI agents on real EHR workflows, like retrieving labs or placing orders. in this benchmark; the best models perform many routine tasks, others fail in messy, real-world data.

In my opinion, model evaluation must shift from the current "simplistic" multiple-choice testing approach to more comprehensive workflow safety and governance.

I am convinced that, while still early, agentic workflow organization will be a massive opportunity within healthcare and life sciences, that is urgently needed.