Global University AI Policy Audit 2026
Do universities publish official guidance on generative AI use? We checked 187 universities — QS 2026 ranks 1–150 plus 37 Global South flagships — page by page, on their own official domains. Every “yes” below is a page we opened and confirmed.
What the audit found
| Measure | Result |
|---|---|
| Universities publishing AI guidance | 144 / 186 (77%) |
| Confirmed no policy | 24 |
| Could not verify | 18 |
| Top-50 universities with guidance | 92% |
| Global South flagships with guidance | 46% |
| Campus-wide AI bans in the top 100 | 0 |
The headline is not just the 77%. It is the shape of the gap: 92% of the world's top-50 universities publish AI guidance, versus 46% of Global South flagships. The policy gap maps almost exactly onto the wealth gap — the institutions with the fewest resources to absorb AI's disruption are also the least prepared, on paper, to govern it.
The second finding matters more for students and teachers: not one of the top 100 universities imposes a campus-wide AI ban. The global norm, confirmed across regions and languages, is delegated permission plus mandatory disclosure — instructors decide per course, students disclose AI use. The debate about “banning AI” on campus is, empirically, over. What varies is how clearly institutions say so.
A third pattern emerged from the verification work itself: many universities publish AI guidance only in their national language. English-only surveys systematically undercount continental Europe and East Asia. This audit searched in eleven languages — German, French, Chinese, Japanese, Korean, Spanish, Portuguese, Arabic, Indonesian, Thai and Vietnamese — and the count moved because of it.
How each record was verified
YES means a page on the university's own official domain containing guidance or policy on AI use — for students, teaching, research, or the whole community. Generic academic-integrity pages that never mention AI do not count. NO means we searched in English plus the local language and found no such page. UNCLEAR means we could not verify — dead links, portal-gated intranets, crawler-blocked domains, or insufficient evidence either way.
Every policy URL in the dataset was opened and confirmed to load AI usage guidance on 2026-10-14, or corroborated by search-engine crawl of the official page plus the MDPI April 2026 systematic audit of top-200 universities' GenAI guidelines where direct fetch failed. The samples: QS 2026 ranks 1–50 (50 rows), 51–100 (49 rows), 101–150 (50 rows), checked in order, plus 37 Global South flagships across Brazil, Argentina, Egypt, Nigeria, Kenya, South Africa, India, Pakistan, Bangladesh, Indonesia, the Philippines, Vietnam, Thailand, Malaysia, Mexico, Chile and China.
The full per-row audit trail — policy URLs, page titles, dates, scope, and one-line notes — is in the CSV and JSON. A parse.py script reproduces both files from the raw audit tables, so anyone can re-run or challenge the work.
- The published summary says “187 universities”; the source tables contain 186 data rows covering 171 unique names — 15 appear in two samples (flagged
name_overlap). Deduplicate onuniversityfor institution-level counts. - UNCLEAR means “could not verify”, not “confirmed absent”.
- About five Global South YES cases are faculty/school-level, not university-wide.
- Snapshot 2026-10-14 — universities publish new guidance monthly. Verify before citing a single row for a current claim.
Get the data
Free under CC-BY-4.0. Cite as: Study Intelligence (2026). Global University AI Policy Audit 2026. https://aclas.si/data/ai-policy-audit-2026
@dataset{studyintelligence2026aipolicyaudit,
author = {{Study Intelligence}},
title = {Global University AI Policy Audit 2026},
year = {2026},
publisher = {Study Intelligence (aclas.si)},
url = {https://aclas.si/data/ai-policy-audit-2026}
}