Education experts offered five predictions about AI’s role in higher ed for 2026, framing the year as one in which institutions will demand measurable ROI, revise pedagogy, and scale governed deployments. Forecasts emphasize a shift from pilots to production use only where AI demonstrably improves retention, revenue, or learning outcomes. At the same time, privacy and governance risks are growing: vendors and campus IT teams warn boards and CFOs that many organizations cannot remove personal data from models, lack kill switches, and cannot enforce purpose limits on AI agents. Health care and education sectors, with high volumes of sensitive student and patient data, face particular exposure. Colleges must accelerate investments in AI governance — data inventories, vendor risk assessments, SBOMs for models, and clear policies on student data use — while aligning teaching‑and‑learning strategies with practical AI use cases that produce measurable student success.