Policy Cards: Machine-Readable Runtime Governance for Autonomous AI Agents
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Abstract (arXiv)
Policy Cards are introduced as a machine-readable, deployment-layer standard for expressing operational, regulatory, and ethical constraints for AI agents. The Policy Card sits with the agent and enables it to follow required constraints at runtime. It tells the agent what it must and must not do. As such, it becomes an integral part of the deployed agent. Policy Cards extend existing transparency artifacts such as Model, Data, and System Cards by defining a normative layer that encodes allow/deny rules, obligations, evidentiary requirements, and crosswalk mappings to assurance frameworks including NIST AI RMF, ISO/IEC 42001, and the EU AI Act. Each Policy Card can be validated automatically, version-controlled, and linked to runtime enforcement or continuous-audit pipelines. The framework enables verifiable compliance for autonomous agents, forming a foundation for distributed assurance in multi-agent ecosystems. Policy Cards provide a practical mechanism for integrating high-level governance with hands-on engineering practice and enabling accountable autonomy at scale.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 2 of its 10 references that are in the map. First posted on arXiv 28 Oct 2025.
Builds on
2 of 10 references.
References · 2
- 2018Model Cards for Model Reportingcited by 1,080
- 2022Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AIcited by 171
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Citing papers per year: 2026: 4.
4 papers.
- 2026From Governance Norms to Enforceable Controls: A Layered Translation Method for Runtime Guardrails in Agentic AIcited by 7
- 2026Governance-Aware Vector Subscriptions for Multi-Agent Knowledge Ecosystemscited by 1
- 2026Traceable Trust for action-ready artificial intelligence in biosciencecited by 0
- 2026Beyond Training: A Feasibility Taxonomy for Inference-Time AI Governancecited by 0
- 2026Beyond Training: A Feasibility Taxonomy for Inference-Time AI Governance9 Sep 2026
- 2026Traceable Trust for action-ready artificial intelligence in bioscience18 Aug 2026
- 2026From Governance Norms to Enforceable Controls: A Layered Translation Method for Runtime Guardrails in Agentic AI6 Apr 2026
- 2026Governance-Aware Vector Subscriptions for Multi-Agent Knowledge Ecosystems21 Mar 2026