Microsoft's AI diagnostic system, MAI-DxO, correctly diagnosed about 83% of complex medical cases in a peer-reviewed study published Thursday in Science — more than double the roughly 36% scored by generalist physicians working individually with reference materials. Microsoft AI CEO Mustafa Suleyman called the result a step toward what he calls 'medical superintelligence.'

The study, 'Sequential diagnosis with language models,' introduces a benchmark called SDBench that turns a case into a step-by-step encounter: the participant starts from a brief summary, then asks questions, orders tests and commits to a diagnosis. On 304 clinicopathological conference cases from the New England Journal of Medicine, MAI-DxO reached 83.2% accuracy (85.5% in peak configurations) against 36.1% for the physicians; on a second test of 325 emergency-department cases from Beth Israel Deaconess Medical Center, it scored 80.3% against 46.8%. MAI-DxO coordinates several AI agents that act like a panel of doctors, and it is model-agnostic — Microsoft tested it over models from OpenAI, Google, Anthropic, Meta and DeepSeek, with the best results on OpenAI's GPT-5 and GPT-5.5, and the orchestration layer alone lifted a GPT-5.5 baseline from 72% to about 87%.

The caveats matter: these are simulations over published case records, not a clinical trial, and cases this complex are normally handled by specialists or physician teams, who were not part of the comparison. Microsoft is now working with Beth Israel Deaconess to evaluate the system in a real hospital setting. 'The biggest challenge in healthcare delivery at the moment is the growing mismatch between demand and supply of medical expertise,' Dominic King, Microsoft AI's vice president of health, told TechCrunch.