Oversight Structures for Agentic AI in Public-Sector Organizations

2025-06-05

AI Summary

This paper addresses the regulatory failure exacerbated by deploying autonomous AI—particularly embodied agents—in the public sector, where traditional siloed, stage-gated approval mechanisms fail to meet three emerging needs: continuous oversight, deep integration of governance into operational workflows, and cross-agency coordination. Adopting a mixed-methods approach—systematic literature review complemented by in-depth interviews with frontline public officials—the study identifies, for the first time, five core AI governance dimensions tailored to public-sector contexts: cross-agency implementation, holistic assessment, enhanced security, operational transparency, and systemic auditing. Based on these, it proposes a novel “agent-oriented regulatory framework” that is institutionally adaptive and technically interoperable. The framework bridges theory and practice, offering actionable guidance for governing autonomous AI systems under real-world institutional constraints—thereby filling a critical gap in the literature on public-sector AI regulation.

Technology Category

• Philosophy and Ethics of AI: AI & Law, Justice, Regulation & Governance
• Multiagent Systems: Agent/AI Theories and Architectures
• Intelligent Robots: Embodied AI

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Search and Retrieval-Augmented AI: Agentic search

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.

Problem

• Addressing intensified oversight challenges from agentic AI in public sectors
• Identifying five key governance dimensions for responsible AI deployment
• Proposing adapted institutional structures for public-sector AI oversight

Innovation

• Cross-departmental AI implementation for governance
• Continuous integrated supervision over episodic approvals
• Enhanced security and systematic auditing protocols