As artificial intelligence rapidly enters classrooms, schools are facing pressure to adopt tools faster than they can fully understand their impact. This session takes a balanced approach to AI in education, grounded in research, child development, and lessons learned from past waves of technology adoption accelerated by COVID.Participants will examine national trends in AI use, school spending, and emerging evidence on inequities, unintended harms, and engagement-driven design. Rather than framing AI as something to race toward or resist, this session centers the need for pre-investment in capacity, guardrails, and shared understanding to avoid repeating mistakes made during large-scale edtech adoption.This session explores who should lead AI decision-making, how to evaluate tools through a developmental and instructional lens, and how to build staff and student readiness before implementation. Participants will leave with strategies to guide AI use thoughtfully, align decisions with student well-being and learning goals, and lead with clarity during uncertainty. This session focuses on leadership, preparation, and systems-level thinking rather than reactive adoption.
