Evaluating Generative AI Policies in Higher Education: Insights from Japan's Top Universities

Abstract

The rapid integration of Generative Artificial Intelligence tools into higher education underscores the urgent need for transparent, responsible, and adaptive institutional governance. This study examines the scope and quality of Generative AI-related policies at Japan's top 50 universities, as ranked in the 2025 QS World University Rankings. Using a 24-item analytical framework derived from established literature, we systematically analyzed publicly available institutional guidelines to assess their comprehensiveness and focus. The results reveal that 37 universities (74%) have issued Generative AI guidelines; however, deficiencies were found in the following areas: specifications of AI model types, documentation protocols for prompts and outputs, detection mechanisms, and procedures for reporting misuse. These deficiencies highlight significant gaps in institutional preparedness to manage emerging AI technologies. Overall, the findings indicate that national universities are leading the development of formal Generative AI governance frameworks, whereas public and private institutions show more fragmented approaches. The study emphasizes the need for comprehensive, transparent, and regularly updated Generative AI policies to ensure the ethical, practical, and future-ready integration of AI in higher education.

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