Comparative analysis of artificial intelligence policies in universities across five countries
Luke Parker, A. Jane Loper, Josh Hayes, Alice Karakas, Steven H. White, Heidi L. Hallman
Abstract
Abstract The rapid integration of artificial intelligence (AI) in higher education has led to significant gaps in policy frameworks across universities worldwide. This study analyzes AI policies at 343 leading universities in Australia, Canada, China, the U.K., and the U.S., selected from the top 1500 institutions globally, as ranked by Times Higher Education for excellence in education across 2024/2025. Using a comparative analysis approach, we examined how these institutions govern the use of AI tools in teaching and learning contexts. Data were gathered from publicly available policy documents, student handbooks, and faculty guidelines, and analyzed using qualitative thematic coding supported by descriptive statistics. Our findings reveal diverse approaches, ranging from outright prohibitions to policies granting instructor's discretion, with notable regional differences influenced by cultural and regulatory factors. Quantitatively, for example, nearly half of universities adopted discretionary policies, while fewer than one in five issued outright bans. This study fills a gap in the literature by providing the first cross-regional analysis of AI policies in higher education, highlighting the absence of a universal framework. These insights offer valuable guidance for institutions to develop flexible, adaptive AI governance models that reflect their unique needs and values.