AI-DRIVEN PUBLIC ADMINISTRATION: EXPERT INSIGHTS ON ADOPTION AND IMPLEMENTATION Cover Image

AI-DRIVEN PUBLIC ADMINISTRATION: EXPERT INSIGHTS ON ADOPTION AND IMPLEMENTATION
AI-DRIVEN PUBLIC ADMINISTRATION: EXPERT INSIGHTS ON ADOPTION AND IMPLEMENTATION

Author(s): Khalima Sansyzbayeva, Laura Ashirbekova, Mónika Imreh-Tóth, Aknur Zhidebekkyzy
Subject(s): Governance, Public Administration, Developing nations
Published by: Fundacja Centrum Badań Socjologicznych
Keywords: artificial intelligence; public administration; AI adoption; data governance; developing countries; Kazakhstan;

Summary/Abstract: Artificial intelligence (AI) is increasingly transforming public administration, yet empirical evidence from developing countries remains limited. This study explores the current use, key challenges, and enabling conditions of AI adoption in Kazakhstan's public administration system. The study employs an exploratory qualitative design based on semi-structured interviews with 20 experts from government, academia, and related professional domains. The data were analyzed using thematic analysis in ATLAS.ti to identify key themes. The findings show that AI adoption is in a transitional stage, supported by strong government initiatives and shifting from digitalization to its use in decision support and predictive analytics for more proactive public services. While a number of pilot projects and practical applications are already in place, broader adoption remains constrained by interrelated barriers, including data limitations, skills gaps, infrastructural constraints, and regulatory uncertainty. The results also identify a corresponding set of enabling conditions, such as institutional support, human capital development, data governance improvements, and cross-sector collaboration, which can facilitate further progress. By linking systemic barriers with corresponding enabling conditions, the study clarifies how AI adoption unfolds in practice and identifies actionable directions for policy and implementation.

  • Issue Year: 19/2026
  • Issue No: 1
  • Page Range: 172-194
  • Page Count: 23
  • Language: English
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