Standard setting is arguably the most consequential decision in exam development, yet passing scores are often based primarily on a single standard-setting exercise involving a relatively small panel of SMEs. As artificial intelligence becomes increasingly integrated into assessment, this session explores how standard setting can evolve through convergent validation: integrating expert judgment, empirical evidence, established methodologies, and AI-assisted analyses. Attendees will learn about limitations of traditional approaches, how multiple standard-setting methods can work together, and how emerging AI approaches can be evaluated as an additional source of evidence to support reliable, transparent, and defensible passing scores.