The Assessment (Self-assessment) Methodology of the University’s Readiness to Use AI

The burgeoning prominence and practical integration of Artificial Intelligence (AI) within contemporary society underscore the imperative to discern its judicious and secure utilization within academic spheres. In this context, the imperative arises to systematically evaluate the use of AI within university operations, navigating its inherent benefits and potential hazards through systematic analysis of its ramifications. The study aims to substantiate the concept of assessment (self-assessment) methodology of the university’s readiness to use AI based on a comprehensive model of the use of AI services and tools in higher education. The focal point of analysis is the operational framework of AI within university activities, while the principal focus pertains to conceptualizing the methodological approach for assessment (self-assessment) of universities’ readiness to employ AI ethically, securely, and effectively. Methodologically, this research draws upon analytical, synthetic, and content analysis methodologies, leveraging UNESCO, OECD, EU directives, and relevant scholarly literature on AI. Theoretical frameworks and methodological tools rooted in sociological inquiry provide the groundwork for the development of assessment methodologies. Consequently, a framework-based approach is posited for assessing (self-assessing) universities’ readiness for AI integration, categorized into distinct thematic domains. The implementation of the methodology, developed based on this concept, promises an objective appraisal of extant AI adoption within university settings.