Artificial intelligence is extending digital administration from electronic record keeping toward prediction, automated service delivery and decision support. This article develops a governance framework for responsible AI adoption in colleges. Using a structured review of higher-education, public-administration, data-governance and AI-ethics literature, the study maps applications across admissions, attendance, examinations, finance, timetabling, student support, infrastructure and institutional planning. It evaluates these applications against five public-governance criteria: efficiency, transparency, accountability, equity and responsiveness. The analysis finds that low-risk automation can reduce delay and repetitive workload, while analytics can improve planning and early academic support. However, high-stakes uses in admissions, discipline, staff evaluation and resource allocation introduce risks of opacity, bias, privacy loss, cybersecurity failure and automation dependence. The paper proposes a layered institutional architecture combining strategy, data governance, approved AI services, human oversight, audit and appeal. It also presents a readiness matrix and phased implementation roadmap suitable for resource-constrained colleges. The central argument is that AI should not be treated as an autonomous administrator; it should function as an accountable decision-support system within democratic, legally compliant and human-supervised college governance.