Аңдатпа
International universities in developing and emerging countries often face multiple challenges, including limited knowledge management, staffing shortages, funding constraints, and limited digital infrastructure, which hinder effective knowledge utilisation. Generative artificial intelligence (GenAI) and large language models (LLMs) can help bridge these gaps by serving as powerful tools. Using an integrative literature review guided by the Technology–Organisation–Environment (TOE) framework, this paper examines policies, directives, and standard operating procedures from 20 universities in the global south. It compares them with international guidelines and market reports on GenAI from organisations such as United Nations Educational, Scientific and Cultural Organization (UNESCO) and the Organisation for Economic Co-operation and Development (OECD), as well as management consulting firms such as McKinsey & Co. and Accenture, published between 2019 and 2024. The findings reveal that many sampled universities lack centralised governance mechanisms, with most relying on informal, department- level efforts. Key gaps include weak alignment with international standards and a narrow focus on GenAI’s potential in education and research beyond addressing plagiarism. This study theoretically expands the TOE framework to include the context of GenAI adoption in universities in developing and emerging countries, emphasising how weak environmental factors and limited institutional readiness shape policy development. The paper also recommends practical steps for universities, such as forming AI task forces, tailoring global guidelines to local settings, and training staff, students, and faculty in the ethical use of GenAI.