Beyond Efficiency: Governance, Accountability, and Institutional Capacity in AI-Driven Public Administration
Author :
Abstract
Digital transformation has evolved from an administrative modernization agenda into a structural dimension of governance, with artificial intelligence (AI) increasingly reshaping how public institutions organize, decide, and interact with citizens. While AI offers important opportunities for responsiveness, innovation, and service improvement, its implications for accountability, legitimacy, transparency, and public trust remain insufficiently understood; this study asks how AI is redefining governance capacity in public administration. Drawing on the literature on public administration, digital governance, and public sector innovation, the study develops a conceptual framework examining both the capacity gains and risks of AI integration, treating digital transformation as a governance challenge involving administrative reform, public value creation, democratic oversight, and institutional adaptation rather than a purely technical matter. The analysis shows that AI can strengthen evidence-based policymaking, accelerate administrative processes, and personalize service delivery, but that these gains may be offset by algorithmic bias, opacity, accountability gaps, and digital exclusion when adopted without adequate institutional safeguards. The paper’s value lies in showing that AI’s contribution to public management depends on the institutional, legal, and normative environment in which it is embedded, which in turn requires regulatory capacity, qualified human resources, and mechanisms for oversight and contestability. Future research should test this framework empirically across diverse administrative contexts.
Keywords
Abstract
Digital transformation has evolved from an administrative modernization agenda into a structural dimension of governance, with artificial intelligence (AI) increasingly reshaping how public institutions organize, decide, and interact with citizens. While AI offers important opportunities for responsiveness, innovation, and service improvement, its implications for accountability, legitimacy, transparency, and public trust remain insufficiently understood; this study asks how AI is redefining governance capacity in public administration. Drawing on the literature on public administration, digital governance, and public sector innovation, the study develops a conceptual framework examining both the capacity gains and risks of AI integration, treating digital transformation as a governance challenge involving administrative reform, public value creation, democratic oversight, and institutional adaptation rather than a purely technical matter. The analysis shows that AI can strengthen evidence-based policymaking, accelerate administrative processes, and personalize service delivery, but that these gains may be offset by algorithmic bias, opacity, accountability gaps, and digital exclusion when adopted without adequate institutional safeguards. The paper’s value lies in showing that AI’s contribution to public management depends on the institutional, legal, and normative environment in which it is embedded, which in turn requires regulatory capacity, qualified human resources, and mechanisms for oversight and contestability. Future research should test this framework empirically across diverse administrative contexts.
Keywords
Artificial intelligence, Digital transformation, Public management, Accountability, Institutional capacity
