Microsoft AI’s diagnostic orchestration system MAI-DxO correctly diagnosed complex medical cases in a simulation more than twice as often as generalist physicians, according to a study published in Science. Mustafa Suleyman, Microsoft AI’s CEO, called the result a step toward “medical superintelligence.” DxO coordinates multiple AI agents that act like a doctor panel: they question a patient, order tests, and debate a diagnosis. In a simulation using complex cases from the New England Journal of Medicine, DxO was correct 83% of the time, versus 36% for primary care doctors and general internists working individually with reference materials. The study’s authors note that such cases are usually handled by specialists or physician teams, who were not included in the comparison.

Microsoft tested DxO with models from OpenAI, Google, Anthropic, Meta, and DeepSeek, with best results from OpenAI’s GPT-5 and GPT-5.5. The study also measured cost. On its own with a short basic prompt, GPT-5 scored 78.9% on complex cases at about $8,400 per case; DxO cut that cost by about $3,000 while raising accuracy by about four points. On emergency department cases, DxO produced little change in accuracy or cost. With GPT-5.5, DxO raised complex-case accuracy from 72% to nearly 87% at a slightly cheaper cost, but emergency department results were again unchanged, at about 85% with or without DxO. DxO helped most on complex cases and with less capable models: Gemini 2.5 Flash scored 46.4% alone but nearly 69% with DxO. Microsoft’s researchers said accuracy gains naturally shrink as models approach the theoretical maximum, and a spokesperson described DxO as addressing the broader challenge of optimizing both accuracy and cost.

Suleyman told TechCrunch that Microsoft is working with Mayo Clinic to train a foundation model for healthcare, with release planned for next year. He said DxO is part of the foundational infrastructure Microsoft is building for healthcare breakthroughs, and predicted that in 2027 “we will be on the verge of a coding style breakthrough for medical records,” allowing streaming predictions about how a record might unfold. He expects healthcare models to get “an order of magnitude better in capability within the next 24 to 36 months,” citing the flywheel of production models, real-world usage, gap identification, and iteration that drove progress in coding and chat.

Microsoft also announced a partnership with Beth Israel Deaconess Medical Center in Boston to evaluate DxO’s clinical reasoning across hospital settings. Dominic King, vice president of Health at Microsoft AI, described the design: patients receive standard care, and those who consent also interact with DxO; Microsoft will compare DxO’s recommendations against human doctors’ decisions. King called it “the biggest study of its kind,” covering emergency and urgent care settings. Google separately published a clinical study with Beth Israel in The Lancet this month evaluating its AMIE conversational diagnostic AI in real-world urgent care visits, with physicians monitoring interactions in real time.

The publication joins Google and OpenAI in claiming that AI can match or outperform doctors, but the study’s own data suggests much of the improvement comes from more powerful underlying models, with Microsoft’s orchestration system adding gains on top. Microsoft defines medical superintelligence as “the capacity to surpass the strongest contemporary human-led health systems in medical reasoning and coordination across the full arc of care.” Microsoft already sells dictation and radiology tools to clinicians and sees DxO as an expansion. Suleyman said this focus could differentiate Microsoft from other frontier labs, and that Microsoft needs “the absolute number one state-of-the-art medical clinical decision support products over the next few years.” The article also notes Suleyman’s long history with medical AI: he co-founded DeepMind, later launched DeepMind Health, joined Microsoft in 2024, and King followed months later.