Many want to know what it take to build a believable, fair, and effective AI-based Standardized Patient? This session examines the full development lifecycle of AI SPs, from training data to performance evaluation and fairness considerations. Explore how these digital entities are tested for fidelity and realism, and what developers and educators must consider to ensure they enhance rather than hinder learning outcomes. The session will highlight interactive components, including polling and collaborative discussion, to encourage thinking around the risks, rewards, and future use cases of AI in simulation-based assessment.