Generative AI Guidelines in Domestic and International Universities: Comparative Analysis and Future Directions

The rapid adoption of generative AI tools such as GPT-4 has prompted universities worldwide to develop institutional guidelines that address both ethical and educational concerns. This study conducts a semi-quantitative analysis of generative AI usage guidelines from 40 universities—20 in Korea and 20 in English-speaking countries—to identify structural patterns, implementation gaps, and effective design principles. Using seven evaluation criteria—including usage scope, ethical responsibility, role-specific guidance, educational innovation, critical thinking, data security, and assessment design—each guideline was scored on a 0–3 scale by four independent raters, achieving high inter-rater reliability (ICC = .953). The results reveal that while many Korean universities emphasize ethical concerns and usage restrictions, they often lack detailed implementation strategies, particularly in areas such as instructional innovation, data security, and alternative assessments. In contrast, international universities tend to provide more actionable and role-differentiated guidance. Based on these findings, the study proposes ten integrated design principles to improve the educational relevance and practical utility of such guidelines. Key recommendations include the establishment of AI literacy education systems, periodic guideline updates, and mechanisms to prevent algorithmic bias and social discrimination. This framework offers a strategic foundation for higher education institutions to develop balanced, pedagogically grounded, and ethically responsible AI policies.