Liaison’s new report, AI in Action, described how higher education enrollment leaders are moving from experimentation to operational deployment of predictive and prescriptive analytics to improve financial aid decisions and student outcomes. The report links intensifying budget pressure and public scrutiny of cost and outcomes to new urgency around tightening aid delivery timelines and responding to demographic shifts. Survey results cited in the report show rapid adoption: 65% of enrollment leaders reported actively using emerging technologies like AI in 2025, up from 40% in 2024, and 61% said their campuses are receptive to AI adoption. It also flagged uneven readiness, noting 56% of respondents do not consider their institution a leader in AI adoption. As a case study, Indiana University of Pennsylvania (IUP) worked with Othot to address declining student engagement and disjointed outreach by using data to model aid scenarios and identify at-risk students. The report emphasizes that successful deployments depend on integrated systems and reliable data, while keeping human judgment and equity at the center. The development points to a practical shift: enrollment leaders increasingly treat AI as infrastructure for operational decisions—targeting, intervention timing, and scenario planning—rather than as an optional analytics layer.