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Three efforts at the intersection of AI and clinical medicine AI models in healthcare have shown strong predictive performance, which has not translated into better care or lower cost — a gap often called the AI chasm. The value of using an AI model is determined by the action pairing it enables: the lead time of the model's prediction or recommendation, whether an effective intervention exists, the work capacity to deliver it, and whether the resulting allocation of resources is fair. The focus, then, is not about building a better model. It is delivery science: making models workflow-aware, evaluating usefulness and fairness during development rather than after deployment, and bringing AI to the clinic safely, ethically, and cost-effectively. There are three efforts aimed at this goal.
