STRATEGIC MANAGEMENT OF ARTIFICIAL INTELLIGENCE INTEGRATION IN HIGHER EDUCATION INSTITUTIONS
Annotatsiya
Artificial intelligence is now widely studied in higher education, but most studies still deal with teaching and learning. Far fewer look at how universities govern AI in their own operations. This conceptual paper reviews selected research on AI leadership, machine learning in university decision making and AI governance, together with national AI policy documents from Azerbaijan, Uzbekistan and India. We identify four conditions for institutional adoption: leadership readiness, data infrastructure, staff capacity and risk management. From them we develop a four-phase framework for university leaders and a short readiness checklist for Phase 1. Our main argument is that data governance and staff preparation should come before AI is used in high-stakes decisions. The framework has not yet been tested empirically.