Generative AI is being rapidly integrated into core academic functions, including teaching, assessment, student support, research workflows and institutional management. This has a direct impact on educational processes and outcomes, given that AI use in education is inherently data-intensive and relies on profiling, learning analytics, prediction and automated or semi-automated decision support. The challenge is that AI is entering all relevant educational domains faster than governance frameworks, evidence bases and institutional capacities can adapt. This working paper explains where the biggest governance gaps lie, what a ‘sandbox’ has to do with education, and why coordinated framework conditions are necessary to enable Higher Education Institutions to research, test and deploy AI responsibly.
Council et al. (Tue,) studied this question.