THE USE OF ARTIFICIAL INTELLIGENCE TO IMPROVE THE EFFICIENCY OF THE REGION MANAGEMENT
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Author(s): | Bazhenov S. I., |
| Number of journal: | 1(74) | Date: | March 2026 |
| Annotation: | The need to improve the quality of management decisions at the regional level is due to the urgent need for a rational allocation of limited resources and ensuring sustainable growth in the social and economic well-being of the territory. In the context of the growing complexity of socio-economic processes, traditional management approaches often turn out to be insufficiently effective, which leads to suboptimal use of budget funds and a slowdown in development. Modern methods of intelligent analysis of large amounts of data (Big Data) — including machine learning and deep analysis of both structured (statistical indicators, time series) and unstructured information (report texts, social networks, geodata) can significantly improve the accuracy of forecasts of key indicators of the region, ranging from economic (GRP, investment, employment) to social (standard of living, migration) and environmental (pollution, resource sustainability). Based on the results of scientific research by domestic and foreign authors, it is proposed to introduce AI technologies to develop models for optimal management decision- making. These models integrate algorithms for adaptive clustering of spatiotemporal characteristics of social processes, multiparametric regression analysis, and techniques for detecting latent relationships in the dynamics of economic indicators. The article discusses in detail the issues of the application of artificial intelligence in the regional development management system using digital methods of territorial planning. The focus is on improving the effectiveness of management decisions through the integration of AI technologies. Compared with traditional methods (expert assessments, static statistics), as well as with digital counterparts and IoT monitoring systems in real time, AI provides automation of the processes of collecting, processing and analyzing big data. This makes it possible to predict socio-economic development over a 3-5-year horizon, optimize budget allocation based on predictive analytics (for example, prioritization of infrastructure projects) and minimize risks (crises, environmental threats). As a result, the introduction of such approaches contributes to the transition to proactive management, increasing the competitiveness of the regions. | ||
| Keywords: | artificial intelligence, digital twin, efficiency of management decisions, management of regional development, competitiveness, regional infrastructure, quality of life, regional forecast, comparative approaches, management risks, forecasting situations, competitiveness of the region |
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| For citation: | Bazhenov S. I. The use of artificial intelligence to improve the efficiency of the region management. Biznes. Obrazovanie. Pravo = Business. Education. Law. 2026;1(74):18—24. DOI: 10.25683/VOLBI.2026.74.1529. |
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