A new set of best practices urges admissions offices to ask why they are deploying AI before choosing tools or rolling out models. The framework emphasizes that AI should be aligned with institutional goals and that admissions teams should evaluate performance, reliability, and governance needs prior to deployment. The guidance comes as universities face growing pressure to modernize recruitment and admissions processes while also confronting compliance, transparency, and fairness obligations. For institutions experimenting with AI-driven messaging, applicant screening, and decision support, the framework signals that governance and rationale should come first. In practice, the message is that AI in admissions cannot be treated as a plug-and-play automation layer; offices must define intended use, acceptable limitations, and accountability for outcomes. As a result, the article functions as a decision checklist for leaders weighing vendor tooling against policy risk.