Integrating generative AI (GAI) into higher education is crucial for preparing a future generation of GAI-literate students. Yet a thorough understanding of the global institutional adoption policy remains absent, with most of the prior studies focused on the Global North and the promises and challenges of GAI, lacking a theoretical lens. This study utilizes the Diffusion of Innovations Theory to examine GAI adoption strategies in higher education across 40 universities from six global regions. It explores the characteristics of GAI innovation, including compatibility, trialability, and observability, and analyses the communication channels and roles and responsibilities outlined in university policies and guidelines. The findings reveal a proactive approach by universities towards GAI integration, emphasizing academic integrity, teaching and learning enhancement, and equity. Despite a cautious yet optimistic stance, a comprehensive policy framework is needed to evaluate the impacts of GAI integration and establish effective communication strategies that foster broader stakeholder engagement. The study highlights the importance of clear roles and responsibilities among faculty, students, and administrators for successful GAI integration, supporting a collaborative model for navigating the complexities of GAI in education. This study contributes insights for policymakers in crafting detailed strategies for its integration.

翻译：将生成式人工智能（GAI）融入高等教育对于培养新一代具备GAI素养的学生至关重要。然而，目前尚缺乏对全球机构采纳政策的全面理解，先前的大多数研究聚焦于全球北方以及GAI的机遇与挑战，且缺乏理论视角。本研究运用创新扩散理论，考察了来自六大全球区域的40所大学在高等教育中的GAI采纳策略。它探讨了GAI创新的特性，包括兼容性、可试验性和可观察性，并分析了大学政策和指南中概述的沟通渠道以及角色与责任。研究结果显示，大学对GAI整合采取积极主动的态度，强调学术诚信、教学与学习提升以及公平性。尽管持谨慎但乐观的立场，但仍需一个全面的政策框架来评估GAI整合的影响，并建立有效的沟通策略以促进更广泛的利益相关者参与。研究强调了教师、学生和管理人员在成功整合GAI中明确角色与责任的重要性，支持一种协作模式来应对教育中GAI的复杂性。本研究为政策制定者制定详细的整合策略提供了见解。