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.

132 The innovation effect relates to the creation of new services and governance frameworks based on AI, while the fiscal effect focuses on budget optimization and the mitigation of misuse, despite associated investment risks. The institutional effect is linked to enhanced transparency through algorithmic oversight and digital footprints, raising governance and ethical challenges. The market effect is characterized by the emergence of GovTech ecosystems and new dependencies, including risks of supplier concentration and vendor lock-in. The outcomes of digitalization depend on the institutional quality and adaptability of the system. AI acts as a catalyst for digital transformation, reinforcing but not replacing organizational change. The economic benefits of AI are largely derived from foundational digital investments and the capacity of organizations to reallocate resources and redesign processes [2; 3]. In the short term, the most immediate economic impact relates to the reduction of transaction costs in the public sector, including automated case categorization, decision support in routine cases, document workflow optimization, queue management, and the automation of data verification processes. However, the ―productivity paradox‖ suggests that such benefits are only realized in the presence of complementary transformations, including data standardization, system integration, process redesign, and workforce upskilling [2; 2]. Given that AI primarily enhances predictive capabilities rather than the normative elements of decision-making, economically optimal frameworks emerge as decision-support systems that improve outcomes through superior inputs while preserving procedural legitimacy in final decisions [1; 5]. The impact of AI on employment in the public sector is reflected in the transformation of task structures rather than direct workforce reduction. Analytical, communicative, and supervisory functions become more prominent, requiring recalibration of personnel policies and competency development [6; 5]. The economic efficiency of AI deployment is inherently linked to the level of digital maturity of the state, including the development of core registries, digital identity systems, and interoperability frameworks. The use of integrated data and