@inproceedings{schmitz-etal-2025-oversight,
    title = "Oversight Structures for Agentic {AI} in Public-Sector Organizations",
    author = "Schmitz, Chris  and
      Rystr{\o}m, Jonathan  and
      Batzner, Jan",
    editor = "Kamalloo, Ehsan  and
      Gontier, Nicolas  and
      Lu, Xing Han  and
      Dziri, Nouha  and
      Murty, Shikhar  and
      Lacoste, Alexandre",
    booktitle = "Proceedings of the 1st Workshop for Research on Agent Language Models (REALM 2025)",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/2025.realm-1.21/",
    doi = "10.18653/v1/2025.realm-1.21",
    pages = "298--308",
    ISBN = "979-8-89176-264-0",
    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."
}