IMPLEMENTATION OF ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN THE EDUCATION SYSTEM: ASSESSMENT OF ECONOMIC EFFECTS, INSTITUTIONAL CONSTRAINTS, AND POTENTIAL RISKS

The integration of artificial intelligence (AI) technologies into the education system is viewed as a driver of greater managerial efficiency and improved quality of educational services; however, it is also accompanied by economic, institutional, and social risks. The purpose of this article is to assess the economic effects of AI adoption (changes in cost structure, reduction of transaction costs, and increased process productivity), identify institutional constraints (legal requirements, personal data protection, allocation of responsibility, and transparency obligations), and systematize potential risks (digital inequality, algorithmic bias, cyber threats, academic dishonesty, and rising hidden costs). The paper proposes an evaluation framework that includes total cost of ownership (TCO) indicators, data quality and managerial performance metrics, as well as a risk-oriented matrix of control measures. It is shown that sustainable economic benefits from AI are achieved primarily through phased implementation, mature data governance, and the presence of institutional regulations that ensure fairness, transparency, and security in AI use. The practical significance of the study lies in proposing a system of indicators and managerial recommendations applicable for justifying AI projects in educational organizations and for assessing their implications at the level of the education system.