A session on MTSS and AI describes how North Kitsap School District is using AI combined with real-time academic, behavioral, and attendance data to strengthen interventions while reducing teacher workload. The district’s approach emphasizes AI-driven feedback tied to support structures rather than standalone automation. The reporting highlights practical implementation concerns that districts face as AI adoption grows: privacy, trust-building, and aligning tools with district goals. The frame is explicitly about making MTSS more data-informed and intervention-focused while maintaining safe and sustainable use. Although focused on K–12, the development is relevant for higher education professionals because many student-success models—including early warning systems and advising workflows—are increasingly data-driven and AI-supported across the education pipeline. For universities, the key takeaway is how district systems are operationalizing AI alongside established student support frameworks, offering a reference point for campus intervention models that rely on cross-functional data (academic progress, engagement, and well-being).