Аңдатпа
Introduction Smart Governance in regional public administration extends beyond service digitalization and depends on digital readiness, citizen-centricity, managerial analytics, AI-automation integration, interagency coordination, and adaptive policy capacity. This study examines these dimensions in Kazakhstan as an emerging digital state characterized by advanced service-platform development and uneven regional administrative capacity. Methods A mixed-methods design was applied to the 2021–2025 period, combining conceptual analysis, review of regulatory and strategic documents, official regional statistics, indicator normalization, descriptive analysis, index construction, and directed qualitative content analysis of digital platforms and administrative practices. Comparable quantitative indicators were assessed across regions, while qualitative evidence was selected through criterion-based purposive sampling. The Smart Governance Index was partially operationalized because complete comparable regional data were unavailable for all dimensions. Results Kazakhstan has established a strong digital and service-platform foundation, but regional Smart Governance remains uneven. In 2024, the difference between the highest and lowest regional digital literacy levels reached 14.31 percentage points. Public satisfaction with government services increased from 75.1% to 92.0%, while eOtinish recorded more than 5 million requests in 2025. However, the ratio of eOtinish requests to the cumulative volume of eGov and eGov Mobile services was approximately 0.97%, indicating that most digital interaction remains transactional rather than analytically integrated into adaptive governance. Discussion The findings demonstrate that advanced digital service provision does not by itself constitute mature Smart Governance. Regional maturity depends on connecting digital infrastructure and citizen interaction with managerial analytics, institutional coordination, human-resource capacity, and feedback-based policy adaptation. The proposed framework therefore distinguishes service-platform maturity from managerial, analytical, and AI-automation maturity and offers a transferable assessment logic rather than a fixed regional ranking.