Towards Smart Public Administration: A TOE-Based Empirical Study of AI Chatbot Adoption in a Transitioning Government Context

Mansur Samadovich Omonov () and Yonghan Ahn ()
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Mansur Samadovich Omonov: Department of Applied Artificial Intelligence, Hanyang University ERICA, Ansan 15588, Republic of Korea
Yonghan Ahn: Department of Architecture and Architectural Engineering, Hanyang University ERICA, Ansan 15588, Republic of Korea

Administrative Sciences, 2025, vol. 15, issue 8, 1-29

Abstract: As governments pursue digital transformation to improve service delivery and administrative efficiency, AI chatbots have emerged as a promising innovation in smart public administration. However, their adoption remains limited, particularly in transitioning countries where institutional, organizational, and technological conditions are complex and evolving. This study aims to empirically examine the key aspects, challenges, and strategic implications of AI chatbots’ adoption in public administration of Uzbekistan, a transitioning government in Central Asia. The study offers a novel contribution by employing an extended technology–organization–environment (TOE) framework. Data were collected through a survey among 501 public employees and partial least squares structural equation modeling was used to analyze data. The results reveal that perceived usefulness, compatibility, organizational readiness, effective accountability, and ethical AI regulation are key enablers, while system complexity, traditional leadership, resistance to change, and concerns over data management and security pose major barriers. The findings contribute to the literature on effective innovation in public administration and provide practical insights for policymakers and public managers aiming to effectively implement AI solutions in complex governance settings.

Keywords: AI chatbots; digital government; innovation management; smart public administration; TOE framework; transitioning countries; Uzbekistan (search for similar items in EconPapers)
JEL-codes: L M M0 M1 M10 M11 M12 M14 M15 M16 (search for similar items in EconPapers)
Date: 2025
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