Anumati defines proof of adherence via versioned PolicyDocument, ConsentRecord, and AdherenceEvent primitives as a non-breaking extension to A2A and MCP protocols.
Governance-as-a-Service.arXiv2025, 2508.18765
6 Pith papers cite this work. Polarity classification is still indexing.
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The paper introduces the Informational Viability Principle and Agent Viability Framework to govern autonomous AI agents by bounding unobserved risks using viability theory, with a new Viability Index for predictive control.
The AAGMM five-level model, validated in 750 simulations, shows higher governance maturity cuts agent sprawl by 94% and risk incidents by 96% while raising task completion rates by 33%.
CUGA introduces a runtime governance architecture that enforces policies at five checkpoints in generalist agent execution pipelines for predictable and compliant behavior.
The EU AI Act narrows accountability for multi-agent AI in critical infrastructure by excluding safety components from key explanation and impact assessment rights, and the paper proposes AgentGov-SC, a three-layer architecture with 25 measures to address this through traceability to existing AI and
AI Trust OS is a proposed always-on operating layer that discovers undocumented AI systems via telemetry and produces continuous zero-trust compliance artifacts for regulations including ISO 42001, EU AI Act, SOC 2, GDPR, and HIPAA.
citing papers explorer
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Anumati: Proof of Adherence as a Formal Consent Model for Autonomous Agent Protocols
Anumati defines proof of adherence via versioned PolicyDocument, ConsentRecord, and AdherenceEvent primitives as a non-breaking extension to A2A and MCP protocols.
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Governing What You Cannot Observe: Adaptive Runtime Governance for Autonomous AI Agents
The paper introduces the Informational Viability Principle and Agent Viability Framework to govern autonomous AI agents by bounding unobserved risks using viability theory, with a new Viability Index for predictive control.
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Governing the Agentic Enterprise: A Governance Maturity Model for Managing AI Agent Sprawl in Business Operations
The AAGMM five-level model, validated in 750 simulations, shows higher governance maturity cuts agent sprawl by 94% and risk incidents by 96% while raising task completion rates by 33%.
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Governance by Construction for Generalist Agents
CUGA introduces a runtime governance architecture that enforces policies at five checkpoints in generalist agent execution pipelines for predictable and compliant behavior.
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Governing What the EU AI Act Excludes: Accountability for Autonomous AI Agents in Smart City Critical Infrastructure
The EU AI Act narrows accountability for multi-agent AI in critical infrastructure by excluding safety components from key explanation and impact assessment rights, and the paper proposes AgentGov-SC, a three-layer architecture with 25 measures to address this through traceability to existing AI and
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AI Trust OS -- A Continuous Governance Framework for Autonomous AI Observability and Zero-Trust Compliance in Enterprise Environments
AI Trust OS is a proposed always-on operating layer that discovers undocumented AI systems via telemetry and produces continuous zero-trust compliance artifacts for regulations including ISO 42001, EU AI Act, SOC 2, GDPR, and HIPAA.