Aknur Zhidebekkyzy

Almaty Management University, Almaty, Kazakhstan

E-mail: a.zhidebekkyzy@almau.edu.kz

ORCID 0000-0003-3543-547X

AI-driven public administration: Expert insights on adoption and implementation

Khalima Sansyzbayeva

Al-Farabi Kazakh National University, Almaty, Kazakhstan

E-mail: halima.sansyzbaeva@kaznu.edu.kz

ORCID 0000-0002-9992-4005

Laura Ashirbekova

Al-Farabi Kazakh National University, Almaty, Kazakhstan

E-mail: laura.ashyrbekova@kaznu.edu.kz

ORCID 0000-0003-0377-7854

Mónika Imreh-Tóth

Széchenyi István University, Győr, Hungary

E-Mail: imreh-toth.monika@sze.hu

ORCID 0000-0002-0094-5827

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.

Received: May, 2025

1st Revision: August, 2025

Accepted: March, 2026

DOI: 10.14254/2071-789X.2026/19-1/9

JEL Classification: O38, H83, O33

Keywords: artificial intelligence, public administration, AI adoption, data governance, developing countries, Kazakhstan