Oversight Structures for Agentic AI in Public-Sector Organizations
This addresses oversight challenges for public-sector organizations deploying agentic AI, but it is incremental as it builds on existing governance issues.
The paper tackles the problem of traditional public sector oversight mechanisms being inadequate for agentic AI systems, finding that these systems intensify three existing governance challenges and proposing approaches to adapt institutional structures and design oversight compatible with public sector constraints.
This paper finds that the introduction of agentic AI systems intensifies existing challenges to traditional public sector oversight mechanisms -- which rely on siloed compliance units and episodic approvals rather than continuous, integrated supervision. We identify five governance dimensions essential for responsible agent deployment: cross-departmental implementation, comprehensive evaluation, enhanced security protocols, operational visibility, and systematic auditing. We evaluate the capacity of existing oversight structures to meet these challenges, via a mixed-methods approach consisting of a literature review and interviews with civil servants in AI-related roles. We find that agent oversight poses intensified versions of three existing governance challenges: continuous oversight, deeper integration of governance and operational capabilities, and interdepartmental coordination. We propose approaches that both adapt institutional structures and design agent oversight compatible with public sector constraints.