Artificial Intelligence in the Economic Management of Higher Education Institutions: International Experience and Trends

The aim of the study is to generalise international experience in applying artificial intelligence (AI) to the economic management of higher education institutions (HEIs) and to identify the trends relevant for Uzbekistan. The methodology combines a case-study analysis of documented institutional practices, a comparative analysis of international regulatory and policy frameworks, and a secondary analysis of Stanford HAI AI Index data. The results show that the strongest documented economic effects arise where predictive analytics is combined with organisational change – as in Georgia State University, where a randomised trial of an AI chatbot reduced “summer melt” by 21%. At the same time, AI investment is highly concentrated geographically, and regulation is shifting from voluntary principles to binding, risk-based rules. The paper concludes with recommendations for Uzbek HEIs.