Proceedings of the International scientific and practical conference ―Research Horizons in the Modern World‖ (March 27-29, 2026) / Publisher website: www.naukainfo.com. – Warsaw, Poland, 2026. - 135 p.

133 standardized information systems reduces coordination costs, improves model accuracy, and enables scalability. In the absence of such foundations, AI initiatives tend to remain fragmented and economically ineffective [7; 8]. Global evidence suggests that the economic benefits of AI are unevenly distributed across countries and sectors, depending on their capacity to integrate technologies into national economic and institutional frameworks. For the public sector, this underscores the need to align policies, standards, and digital infrastructure with international frameworks to enhance competitiveness and governance effectiveness [5; 8]. The implementation of artificial intelligence in the public sector entails a wide range of institutional and economic challenges. Among these, notable are the costs associated with trust, transparency, and security, the phenomenon of vendor lock-in, and potential risks related to the unequal distribution of benefits alongside labor market transformation. Policies aimed at effective implementation must adequately account for these factors by establishing data standards, promoting competitive procurement practices, and developing performance evaluation mechanisms [10; 8]. In the absence of interoperable registries and high-quality data, AI initiatives often stagnate at the pilot stage: models fail to align with procedural adjustments, data are not seamlessly integrated across departments, and manual workarounds reduce potential benefits. This observation aligns with the conceptualization of digital transformation as a systemic phenomenon (rather than a set of isolated IT initiatives) [2] and supports the view that interoperability constitutes a fundamental institutional principle of the digital state [7]. Thus, the implementation of AI in the public sector generates a multidimensional economic effect that materializes only under conditions of integrated technological, institutional, and human capital transformation. The key determinant is not the technology itself, but its embeddedness within governance systems, including data quality, interoperability, and institutional adaptability. In the absence of these conditions, the effects of digitalization remain fragmented and fail to ensure sustainable transformation.