AI Agent Governance: A Field Guide
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Abstract (arXiv)
This report serves as an accessible guide to the emerging field of AI agent governance. Agents - AI systems that can autonomously achieve goals in the world, with little to no explicit human instruction about how to do so - are a major focus of leading tech companies, AI start-ups, and investors. If these development efforts are successful, some industry leaders claim we could soon see a world where millions or billions of agents autonomously perform complex tasks across society. Society is largely unprepared for this development. A future where capable agents are deployed en masse could see transformative benefits to society but also profound and novel risks. Currently, the exploration of agent governance questions and the development of associated interventions remain in their infancy. Only a few researchers, primarily in civil society organizations, public research institutes, and frontier AI companies, are actively working on these challenges.
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). First posted on arXiv 27 May 2025.
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Citing papers per year: 2025: 3; 2026: 5.
8 papers.
- 2025TRiSM for Agentic AI: A Review of Trust, Risk, and Security Management in LLM-based Agentic Multi-Agent Systemscited by 59
- 2025BetaWeb: Towards a Blockchain-enabled Trustworthy Agentic Webcited by 7
- 2026LLM Agents in Law: Taxonomy, Applications, and Challengescited by 5
- 2026Cheap Code, Costly Judgment: A Case Study on Governable Agentic Software Engineeringcited by 2
- 2025A Conceptual Framework for AI Capability Evaluationscited by 0
- 2026Human Attribution of Causality to AI Across Agency, Misuse, and Misalignmentcited by 0
- 2026Skillsets on the Chain: A Blockchain-based Zero-Trust Framework for Agentic AI Networkingcited by 0
- 2026Testing and Evaluation of Agentic AI Systems In Military Command and Controlcited by 0
- 2026Testing and Evaluation of Agentic AI Systems In Military Command and Control20 Aug 2026
- 2026Skillsets on the Chain: A Blockchain-based Zero-Trust Framework for Agentic AI Networking31 Jul 2026
- 2026Cheap Code, Costly Judgment: A Case Study on Governable Agentic Software Engineering1 Jul 2026
- 2026Human Attribution of Causality to AI Across Agency, Misuse, and Misalignment17 Feb 2026
- 2026LLM Agents in Law: Taxonomy, Applications, and Challenges8 Jan 2026
- 2025BetaWeb: Towards a Blockchain-enabled Trustworthy Agentic Web19 Aug 2025
- 2025A Conceptual Framework for AI Capability Evaluations23 Jun 2025
- 2025TRiSM for Agentic AI: A Review of Trust, Risk, and Security Management in LLM-based Agentic Multi-Agent Systems4 Jun 2025