The most comprehensive database of AI policies across 100+ top US universities, searchable, comparable, and updated from primary sources.
As AI transforms higher education, universities across the United States are developing policies to guide its responsible use. But finding, understanding, and comparing these policies is fragmented and time-consuming.
The Trinka AI Policy Repository brings together AI governance policies from top US universities into a single, searchable hub, built for students, faculty, researchers, and administrators who need factual, clear, and reliable information about how their institution governs AI use in coursework, research, academic integrity, and institutional operations.
Explore AI governance policies from 100+ top US research universities, covering coursework, research ethics, data protection, and more.
Shows how many of the 12 AI policy categories a university has formally defined. 100% means all 12 categories are addressed. Color indicates completeness: green (75%+), amber (50%+), orange (25%+), gray (below 25%).
Indicates the university's position on AI tool usage in coursework and assignments, based on their published policy for category U1.
Shows whether the university requires students to disclose and cite AI usage in academic submissions, based on category U8.
Indicates whether the university uses AI detection tools (e.g., Turnitin) or manual review to identify unauthorized AI use, based on category U9.
Public universities are state-funded institutions. Private universities are independently funded. Use the filter chips above to view only public or private universities.
Each university is evaluated across 12 AI policy categories spanning 4 domains: Teaching & Learning (U1-U4), Research (U5-U7), Academic Integrity (U8-U9), and Institutional & Administrative (U10-U12). Click "View AI Policy" on any university to see the full breakdown.