Universities have embedded machine learning across recruitment, scheduling, assessment and student support, yet most lack a comprehensive inventory or governance framework for those systems, sector analysts say. A report on institutional AI use found that admissions algorithms, chatbots, learning‑analytics dashboards and automated early‑warning systems are shaping decisions without clear accountability or transparency. At the same time, Microsoft researchers published a list identifying 40 jobs with high AI applicability — including teaching‑adjacent roles and knowledge workers — highlighting how academic workforce planning and career services must adapt. The intersection of institutional automation and labour‑market exposure to generative AI raises immediate questions for curriculum design, faculty workload and regulatory compliance. Universities are being urged to map end‑to‑end AI dependencies, designate institutional owners for automated decisions and update governance to include procurement, data protections and academic oversight. Without that work, institutions risk operational failures and legal exposure as AI becomes the operating system of higher education.