APPLICATION OF ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN ASSESSING REGIONAL SOCIAL STRATIFICATION

This article analyzes, from an economic-sociological perspective, a conceptual platform designed to identify and monitor the level of social stratification across regions using artificial intelligence (AI) technologies. The study develops a set of indicators for measuring regional stratification based on a synthesis of existing literature, defines principles of data integration and anonymization, and proposes the RISI (Regional Social Stratification Index). Pilot tests calculated the RISI for several regions using administrative and survey data, identifying regions with high, medium, and low levels of stratification. SHAP interpretation shows that income dispersion, educational attainment, internet speed, and the digital skills index are the most influential factors affecting the RISI. Clustering results and anomaly detection confirm the practical value of the platform in identifying regional disparities and directing policy interventions more effectively.