Colleges and universities are expanding the use of AI tools designed to identify at‑risk students, personalize learning, offer 24/7 support and improve retention. Institutions report early wins in predictive analytics and automated outreach that help advisors triage interventions and reduce summer melt. The technologies range from early‑warning dashboards to AI tutors and automated case‑management assistants. While promising, adoption raises questions about data privacy, algorithmic bias, and the need for human oversight to ensure interventions are equitable and culturally responsive. Student‑success leaders should prioritize transparent validation of models, meaningful consent and opt‑outs, training for advising staff, and pilot evaluations that measure outcomes for Pell‑eligible and first‑generation students before scaling.