A new installment in Liaison’s AI-in-higher-ed coverage highlights how universities are moving from pilots to operational use of predictive and prescriptive analytics for enrollment and financial aid decisioning. The report ties adoption to tightening budgets, public scrutiny of outcomes, and continued effects from FAFSA processing delays and demographic shifts. Liaison reported that in 2025, 65% of enrollment leaders said they were using emerging technologies like AI, up from 40% in 2024, and that 61% said campuses are receptive to AI adoption. Readiness is uneven, however, with more than half of respondents saying their institutions are not leaders in AI adoption and many citing the need for clearer goals, integrated systems, and reliable data. The report’s featured case is Indiana University of Pennsylvania (IUP), where outreach and engagement were described as disjointed despite having rich student data. IUP said it began working with Othot to convert insights into actions supporting engagement and retention. The takeaway for higher education operations is that “AI readiness” is less about model capability and more about execution in workflows—how institutions intervene at-risk students and quantify effects of aid and enrollment decisions while maintaining human judgment and equity considerations.