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    <abstract>This paper finds that agentic AI systems intensify 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 mechanisms and design agent architectures compatible with public sector constraints.</abstract>
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%0 Conference Proceedings
%T Oversight Structures for Agentic AI in Public-Sector Organizations
%A Schmitz, Chris
%A Rystrøm, Jonathan
%A Batzner, Jan
%Y Kamalloo, Ehsan
%Y Gontier, Nicolas
%Y Lu, Xing Han
%Y Dziri, Nouha
%Y Murty, Shikhar
%Y Lacoste, Alexandre
%S Proceedings of the 1st Workshop for Research on Agent Language Models (REALM 2025)
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-264-0
%F schmitz-etal-2025-oversight
%X This paper finds that agentic AI systems intensify 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 mechanisms and design agent architectures compatible with public sector constraints.
%R 10.18653/v1/2025.realm-1.21
%U https://aclanthology.org/2025.realm-1.21/
%U https://doi.org/10.18653/v1/2025.realm-1.21
%P 298-308

Markdown (Informal)

[Oversight Structures for Agentic AI in Public-Sector Organizations](https://aclanthology.org/2025.realm-1.21/) (Schmitz et al., REALM 2025)

• Oversight Structures for Agentic AI in Public-Sector Organizations (Schmitz et al., REALM 2025)

ACL

• Chris Schmitz, Jonathan Rystrøm, and Jan Batzner. 2025. Oversight Structures for Agentic AI in Public-Sector Organizations. In Proceedings of the 1st Workshop for Research on Agent Language Models (REALM 2025), pages 298–308, Vienna, Austria. Association for Computational Linguistics.