# AI Agent Governance: A Field Guide

arXiv: https://arxiv.org/abs/2505.21808 · HTML: https://mlsanity.com/paper/2505.21808/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 May 2025.

## Built on by (most cited first, 8 of 8)

- [TRiSM for Agentic AI: A Review of Trust, Risk, and Security Management in LLM-based Agentic Multi-Agent Systems](https://mlsanity.com/paper/2506.04133/) (2025)
- [BetaWeb: Towards a Blockchain-enabled Trustworthy Agentic Web](https://mlsanity.com/paper/2508.13787/) (2025)
- [LLM Agents in Law: Taxonomy, Applications, and Challenges](https://mlsanity.com/paper/2601.06216/) (2026)
- [Cheap Code, Costly Judgment: A Case Study on Governable Agentic Software Engineering](https://mlsanity.com/paper/2607.01087/) (2026)
- [A Conceptual Framework for AI Capability Evaluations](https://mlsanity.com/paper/2506.18213/) (2025)
- [Human Attribution of Causality to AI Across Agency, Misuse, and Misalignment](https://mlsanity.com/paper/2603.13236/) (2026)
- [Skillsets on the Chain: A Blockchain-based Zero-Trust Framework for Agentic AI Networking](https://mlsanity.com/paper/2608.00104/) (2026)
- [Testing and Evaluation of Agentic AI Systems In Military Command and Control](https://mlsanity.com/paper/2608.20597/) (2026)

## 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.