As leaders in precision medicine and clinical trial design, we recognize the significant potential of artificial intelligence (AI) in transforming patient care. However, true transformation hinges on establishing the same rigorous evidentiary standards that govern new drug approvals. While AI tools promise enhanced disease diagnosis, personalized treatment, and improved patient outcomes, their adoption faces challenges due to a lack of foundational trust. This trust deficit stems from a discrepancy in the evidentiary requirements for AI compared to traditional therapies. A recent analysis revealed that out of 903 FDA-approved AI-enabled medical devices, merely 12, or just over 1%, were backed by randomized controlled trial (RCT) data. For AI to be fully embraced in the medical community, a commitment to strict evidence standards is imperative, ensuring patient safety and effectiveness. Addressing these gaps will be essential for integrating AI into clinical practice and realizing its full potential in healthcare.
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