Student Use of Generative AI in Higher Education: Patterns, Gaps, and Institutional Readiness

Introduction: This study examines how widely students are using generative AI tools in higher education and whether they feel prepared and supported by their institutions in doing so. Methods: This study used descriptive analysis of survey responses from 3,839 students across 16 countries to examine AI use, preparedness, and institutional support. Results: Most students (86%) reported using AI, yet few felt prepared (23%) and many cited inadequate institutional guidance. Discussion: Findings reveal a clear gap between students’ rapid adoption of AI tools and limited institutional readiness to support them. Limitations: The study relies on voluntary, self-reported, cross-sectional data that may involve selection bias and cannot establish causality. Conclusions: Results highlight the need for stronger AI literacy, updated assessments, and clearer institutional guidance for responsible AI use in higher education.