Trust Infrastructure for Production Healthcare AI

Healthcare AI is moving beyond copilots toward agents embedded in clinical, operational, and life-sciences workflows. The article argues that production readiness depends less on model choice than on trust infrastructure: evidence grounding, source provenance, no-answer behavior, expert validation, secure data access, and measurable evaluation. Case studies report physician-accepted chart extraction, reduced review times, and faster delivery, but also show that these outcomes rely on governed architectures and clear human decision gates. Leaders should treat evaluation, data sovereignty, and workflow integration as core design requirements rather than controls added after deployment.