Purpose: This study examines academic production on guidelines and frameworks for the governance of generative artificial intelligence in higher education institutions. Design/methodology: A scoping review was conducted utilizing the Web of Science database, analyzing publications from 2023 and 2024. Findings: The results were organized into four thematic clusters: guidelines and frameworks, challenges in the adoption of generative artificial intelligence governance in higher education, stakeholder perceptions, and research gaps. Research implications: The study provides insights and could serve as a reference for adopting generative artificial intelligence in other institutions. Originality/value: This research contributes to the body of studies focused on the integration and governance of generative artificial intelligence in higher education institutions.
No takes yet. Share an insight, caveat, or question.
Gomes et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: