As AI tools begin supporting clinicians in learning, reflection, and everyday workflows, healthcare organizations must ensure these systems strengthen skills while reducing legal, ethical, and reputational risk. This session presents a governance-first framework for AI-enabled clinician coaching, designed to be model-agnostic and adaptable across use cases.

This framework integrates several foundational safeguards: intent classification to ensure interactions stay within approved educational boundaries; safety filtering and guardrails that prevent harmful or misleading outputs; and a rubric-based knowledge-layer reasoning process that anchors the AI’s explanations and feedback in trusted medical standards. Building on this, the orchestration layer supports adaptive nudge sequencing, personalized prompts that help clinicians practice safe, effective reasoning chains over time.

Participants will gain a practical, easy-to-adapt blueprint for designing or evaluating AI coaching systems that improve clinician confidence and competence while embedding transparency, safety, and responsible governance at critical steps.