Evaluating the readiness of public institutions for AI-Driven decision making: A framework for adaptive governance

Kurhayadi Kurhayadi ()

Edelweiss Applied Science and Technology, 2025, vol. 9, issue 4, 1569-1580

Abstract: The rapid advancement of artificial intelligence (AI) technologies is reshaping decision-making processes across various sectors, including public administration. However, the readiness of public institutions to adopt AI-driven decision-making remains a critical and underexplored area. This study employs a systematic literature review method to evaluate the current state of institutional readiness for AI adoption within the public sector, while simultaneously proposing a conceptual framework grounded in adaptive governance principles. By synthesizing findings from peer-reviewed journals, policy reports, and empirical studies published between 2013 and 2023, this article identifies key dimensions of readiness, including institutional capacity, digital infrastructure, regulatory frameworks, human resource competencies, and ethical safeguards. The review reveals significant disparities across countries and institutional levels, with many public entities struggling to integrate AI in a manner that aligns with democratic accountability, transparency, and citizen trust. Furthermore, the study highlights the growing relevance of adaptive governance approaches that emphasize flexibility, iterative learning, and stakeholder collaboration in navigating the complexities of AI integration. The proposed framework serves as a diagnostic tool for assessing institutional preparedness and guiding future reforms. Ultimately, this article contributes to the literature on AI in public administration by offering actionable insights for policymakers, administrators, and scholars seeking to foster responsible and adaptive AI adoption in public institutions.

Keywords: Adaptive governance; Artificial intelligence; Digital transformation; Institutional readiness; Public administration; Public sector innovation. (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:ajp:edwast:v:9:y:2025:i:4:p:1569-1580:id:6335

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