Public Sector Knowledge Systems and Agentic AI: Institutional Learning and Policy Innovation
Abstract
Public sector knowledge systems are undergoing rapid transformation as artificial intelligence (AI) becomes embedded in governance processes. AI technologies increasingly support administrative decision-making, policy analysis, and service delivery by enabling data-driven insights, predictive analytics, and automation within government institutions. As digital infrastructures mature, governments are moving beyond basic e-government models toward integrated knowledge ecosystems that enhance analytical capacity, cross-agency coordination, and citizen engagement. This article examines the intersection of public sector knowledge systems and “agentic AI”—AI systems capable of autonomous analysis, adaptive feedback generation, and iterative problem-solving. It argues that agentic AI represents a qualitative shift from rule-based automation toward dynamic institutional learning. By embedding AI within governance platforms, participatory mechanisms, and knowledge management processes, public institutions can strengthen policy experimentation, accelerate learning cycles, and foster evidence-informed innovation. However, technological capability alone does not guarantee institutional transformation. Effective integration depends on organizational capacity, legal and ethical safeguards, civil servant competencies, and leadership that aligns macro-institutional frameworks with micro-level implementation practices. Without deliberate institutional design, AI adoption may reinforce bureaucratic inertia or exacerbate governance risks related to transparency, accountability, and bias. The article proposes a conceptual framework linking knowledge infrastructures, agentic AI capabilities, and institutional learning loops to explain how public administration can transition from digitization and automation toward adaptive, innovation-oriented governance.
Keywords: Agentic AI; Public Sector Knowledge Systems; Institutional Learning; Policy Innovation; Digital Government; Knowledge Management; Governance Platforms; Policy Capacity; Administrative Reform; Ethical AI Governance
