FORMATION OF A SYSTEM FOR DIGITAL MONITORING OF SOCIO-ECONOMIC
INDICATORS USING ARTIFICIAL INTELLIGENCE

Anna KRYMSKA

Chernivtsi Institute of Trade and Economics of SUTE, Chernivtsi

https://orcid.org/0000-0001-6410-9476

DOI: http://doi.org/10.34025/2310-8185-2026-1.101.03

Keywords: intelligent systems, machine learning, digital indicators, forecasting models, data-driven governance, state registers, automated analytics, information infrastructure.

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Summary

The relevance of the research stems from the growing need for data-driven governance in countries facing structural turbulence, where wartime conditions in Ukraine make traditional analytical tools insufficiently accurate and responsive, underscoring the role of AI in collecting, processing, and forecasting socio-economic indicators.

The study aims to substantiate the conceptual foundations for an integrated intelligent monitoring system capable of automated analysis of multidimensional socio-economic data, early risk identification, and improved evidence-based public decision-making. The methodology is grounded in systemic and comparative analysis, the generalization of scientific approaches, content analysis of statistical and regulatory sources, and structural-logical modeling of the integrated digital monitoring framework.

The study develops a conceptual model of digital monitoring integrating data acquisition (open data, state registers, satellite data), analytical and forecasting modules (ML, neural networks, NLP), risk identification, and decision support. AI integration enhances forecast accuracy, reduces reaction lags, and enables early detection of structural imbalances. Key barriers include low data quality, limited digital infrastructure, a shortage of specialists, and the need for ethical and regulatory frameworks aligned with the EU AI Act. Overall, the intellectualization of monitoring systems strengthens evidence-based governance and supports proactive responses to socio-economic risks.

The findings provide a foundation for developing a national digital monitoring system capable of ensuring timely forecasting and enhancing the effectiveness of public policy in the context of Ukraine’s European digital integration. Further studies should focus on improving data quality assessment methods, developing ethical and security frameworks for AI application, and adapting intelligent monitoring systems to the sectoral needs of public administration.

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Biographies of authors:

Anna KRYMSKA,

Chernivtsi Institute of Trade and Economics of SUTE

Candidate of Technical Sciences, Associate Professor,

Associate Professor Department of Management, Marketing and Logistics

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