New approaches to analyzing the state of rural areas have been proposed, based on a combination of advanced methods for processing geospatial data, machine learning, and artificial intelligence. A methodology for clustering villages, analyzing the development level of rural communities, and identifying directions for infrastructure improvement has been developed. This, in turn, allows for the assessment of infrastructure accessibility, taking into account not only distances but also topological connections between objects. Such an approach simplifies the analysis by enabling the automatic identification of underdeveloped areas. Thanks to open data sources (OSM, HDX), the model is easily scalable and can be applied to different regions. The methodology for assessing the quality of life in rural settlements in Ukraine using geospatial analysis makes it possible to aggregate data on the remoteness of villages from vital facilities such as hospitals, schools, roads, utilities, and more. The proposed approach provides a strong foundation for decision-making regarding the restoration and modernization of rural infrastructure. The assessment of rural development in Ukraine under wartime conditions, using GIS, multicriteria analysis, and AI-based virtual experts, allows the obtained results to be used for shaping policies on the rational allocation of resources for the effective restoration of well-being and development of rural areas. Proposed information technologies for geospatial analysis of rural community development. In particular, an interactive map of rural community development index values has been created, based on multicriteria decision-making (MCDM) and graph models, which enables the evaluation of the current state of rural infrastructure for each selected criterion. For visualization of the results, a geoportal has been implemented in the CREODIAS cloud environment.