School leaders are rich in data but often short on time to translate it into meaningful action. This interactive session introduces a practical framework for using AI to move from data analysis to instructional improvement — without adding to the leadership workload. Participants will engage in hands-on workflows across three domains: (1) Data analysis — using AI to identify patterns in student performance, pinpointing implementation gaps aligned with MTSS (2) Intervention design — developing evidence-based, context-responsive strategies that address a school's unique challenges (3) Leadership communication — translating observations and trends into actionable teacher feedback, coherent PD planning, and transparent community updates. Grounded in research, this session emphasizes the human-in-the-loop principle: AI supports decision-making, but educators lead. Participants leave with a replicable workflow they can implement immediately in their buildings.