Universities have embedded machine learning and automation across recruitment, admissions, scheduling, assessment and student support — but many campuses lack a central inventory or governance for those systems. Institutional leaders report fragmented responsibility among IT, registry and academic committees, leaving accountability gaps for algorithmic decisions that affect admissions, grading and early-warning interventions. A review of campus practices found chatbots fielding late-night inquiries, automated filters scoring applicants, scheduling algorithms matching student numbers to rooms, and analytic dashboards classifying student risk without clear human oversight. Experts warn that treating AI as an optional tool ignores its emerging role as an operating system beneath campus processes. The piece calls for institution-wide audits, clearer ownership structures, and transparency about which automated decisions materially affect students — practical steps campuses can adopt to reassert governance over mission-critical technology.