Stanislav Dobrolezha, Maria KUCHERIAVA, Serhii Lisovyi
Purpose. The purpose of the study is to develop an integrated analytical framework for embedding Artificial Intelligence (AI) into quality management systems (QMS) of Higher Education Institutions (HEIs), ensuring analytical support for sustainable IT business processes and enabling the transition toward circular economy models. Methodology. The study is based on a multi-stage research design that combines system analysis, structural-functional and comparative analysis, abstraction, and modeling. A risk-oriented approach is applied to identify and assess challenges related to AI implementation, while content analysis is used to systematize existing scientific contributions. HEIs are conceptualized as complex socio-economic systems, allowing for the integration of AI technologies, QMS elements, and IT business processes within a unified analytical framework. Results. The results confirm that AI acts as a key driver in transforming QMS from static, compliance-based models into adaptive, data-driven, and predictive systems. AI technologies are systematically embedded across core QMS elements, including quality planning, assurance, control, improvement, risk management, and internal audit. This integration enhances decision-making accuracy, enables real-time monitoring, strengthens internal control mechanisms, and supports proactive risk management. Additionally, AI-driven IT business processes contribute to the implementation of circular economy principles through resource optimization, digitalization, and waste reduction. Practical implications. The proposed framework provides HEIs with a structured and applicable model for implementing AI-driven QMS, incorporating internal audit and risk management mechanisms. It supports improved governance, operational efficiency, compliance with international standards, and alignment with sustainability objectives. Value / originality. The study offers a novel, integrated approach that links AI, quality management systems, and IT business processes with circular economy principles. Unlike fragmented existing research, it provides a comprehensive, system-based perspective on the transformation of higher education management.