Integrating Artificial Intelligence into Public Administration: Challenges and Vulnerabilities

Anca Florentina Vatamanu () and Mihaela Tofan
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Anca Florentina Vatamanu: Faculty of Economics and Business Administration, Alexandru Ioan Cuza University, 700107 Iasi, Romania
Mihaela Tofan: Faculty of Economics and Business Administration, Alexandru Ioan Cuza University, 700107 Iasi, Romania

Administrative Sciences, 2025, vol. 15, issue 4, 1-23

Abstract: This study explores the application of artificial intelligence (AI) in public administration, examining its potential to enhance efficiency, sustainability, and resilience in government actions. The research develops a theoretical framework to assess the relationship among AI integration, governance improvements, and economic benefits, as measured by key components of the Digital Economy and Society Index (DESI). Utilizing factor analysis and ordinary-least-squares (OLS) regression, this study provides empirical insights into how AI-driven applications contribute to public service delivery and economic growth. The findings highlight that AI has the potential to improve governance significantly. Still, the transition to AI-enhanced public administration is accompanied by challenges such as algorithmic bias, cybersecurity risks, workforce adaptation, and ethical issues. This study emphasizes the need for robust governance structures, comprehensive security measures, and active public involvement to address these challenges. By proposing a clear framework for managing AI integration, this research contributes to the literature on digital transformation in the public sector and offers actionable insights for policymakers and practitioners. Future research should examine AI’s broader applications across diverse public sector contexts, ensuring that governance remains aligned with democratic values, public trust, and long-term sustainability.

Keywords: artificial intelligence; public administration; governance frameworks; AI governance; service delivery (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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