<p>The growing integration of Artificial Intelligence (AI) into public administration is fundamentally transforming governance processes. This growth underscores its importance for both scholarship and practice. Despite expanding interdisciplinary research, a significant gap remains in systematically linking AI innovations with established public administration frameworks, particularly in understanding how algorithmic systems reshape governance paradigms and institutional practices. The article addresses this gap by examining the transformative effects of AI on governance structures and administrative processes. The goal is to develop a conceptual framework for understanding algorithmic governance within public administration and to evaluate its implications for public value creation. It employs a qualitative, theory-driven approach, based on a systematic review and analytical synthesis of interdisciplinary literature across public administration and AI scholarship. The article finds that AI is driving a transition from hierarchical, rule-based systems to data-driven and adaptive governance models. Furthermore, the findings reveal significant gaps in existing accountability mechanisms due to the opaque and distributed nature of algorithmic decision-making. The article concludes that the effective integration of AI in public administration depends on the adoption of a public value–centred governance framework. The article contributes to both public administration and AI scholarship, offering a normative and institutional pathway for aligning technological innovation with democratic governance.</p>