The adoption of artificial intelligence (AI)-powered tools is accelerating rapidly across all layers of healthcare systems. Predictive models, decision support tools and generative tools have entered clinical environments 1 , and large language models are increasingly being used by the general public to seek medical information and advice 2 .
Yet evidence that AI tools create value for patients, providers or health systems remains scarce. Nonetheless, in publications, and in product materials, claims about clinical impact are increasingly more common, even though there is no clear agreement on what level of evidence should be required before such claims are considered credible.
The result is not only scientific uncertainty but also often premature implementation and adoption. If AI is to improve care meaningfully, the field must begin to systematically and consistently link claims of impact to appropriate, proportional evidence.
A framework for how AI medical technologies should be evaluated, by what metrics and against which benchmarks is urgently needed.
Nature Medicine published a clinical update in Research Highlights on 21 Apr 2026.
The item focuses on Show us the evidence for the value of medical AI.
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