Oversight Structures for Agentic AI in Public-Sector Organizations

TL;DR

This paper examines how agentic AI systems challenge traditional public sector oversight, emphasizing the need for integrated, continuous, and cross-departmental governance to ensure responsible deployment.

Contribution

It identifies key governance dimensions for agent oversight and evaluates existing structures, proposing adaptations for public sector constraints.

Findings

Agentic AI intensifies oversight challenges

Existing oversight structures are insufficient for continuous supervision

Proposed governance adaptations improve agent oversight

Abstract

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.