AI Governance Guides
All articles in the AI Governance category
Audit Copilot, Agentforce, and Custom AI Agents
Apply one audit method to Microsoft Copilot, Salesforce Agentforce, and custom AI agents, with platform evidence, checklists, and a valid schema example.
AI Agent Audit Software: Requirements, Categories, and a Neutral Buyer Guide
Evaluate AI agent audit software with 12 requirements, current vendor categories, procurement tests, stack guidance, and a downloadable buyer checklist.
AML Alert-Triage Agents: Controls and Evidence
Govern one AML alert-triage run from intake through disposition, maker-checker review, recovery, and sealed evidence with testable policy thresholds.
Human Oversight for AI Agents: When Is Approval Required?
Decide when an AI agent can proceed, needs review, or must stop. Use a four-outcome policy table, maker-checker workflow, evidence schema, and playbook.
NIST AI RMF vs EU AI Act vs ISO/IEC 42001: Which Applies to You
Compare NIST AI RMF, the EU AI Act, and ISO/IEC 42001 by authority, scope, assurance, evidence, and agent-control coverage.
AI Agent Incident Response Playbook: Contain, Roll Back, Evidence, Report
A practical AI agent incident response playbook for containment, safe rollback, evidence preservation, recovery, and EU AI Act Article 73 reporting decisions.
The AI Agent Register: A Cross-Platform Inventory Template for Copilot, Agentforce, and Custom Agents
Download a cross-platform AI agent inventory template covering ownership, autonomy, permissions, systems, approval rules, evidence, review triggers, and known gaps.
Runtime AI Governance: Before, At, and After
Runtime AI governance controls agent actions as systems run. See how it differs from observability, guardrails, and governance of record.
The Hugging Face AI Agent Breach: 17,000 Recorded Events, Phase by Phase
What Hugging Face disclosed about an intrusion driven by an autonomous AI agent, what OpenAI later attributed to its own models, and which controls have to run before an agent action executes.
How to Audit an AI Agent System: An Enterprise Framework for Production
A fieldwork-ready, 12-domain AI agent audit framework for scope, ownership, authority, runtime controls, sampling, evidence, findings, and follow-up.
AI Agent Accountability Matrix: Who Owns What in Production
A field-ready accountability matrix for 13 AI agent governance roles across design, approval, release, runtime, incidents, change, and retirement.
AI Agent Audit Program: Scope, Sampling, Evidence, and Reporting
A fieldwork-ready internal audit program for AI agent scope, population completeness, risk assessment, control testing, sampling, evidence, findings, and follow-up.
SAFR, Explained: Inside MAS's Runtime Framework for AI Agents in Finance
SAFR is MAS BuildFin.ai's runtime governance reference for AI agents in finance. Inside: four components, four dispositions, envelopes, and mandates.
The AML Agent Control & Evidence Map: Every Agent Action, Its Control Gate, Its Accountable Human, and Its Sealed Evidence
The canonical table mapping each AML and payments AI-agent action to its control gate, accountable human, and sealed evidence record, cross-referenced to DORA, the AMLR, and Wolfsberg.
Why Static AI Governance Breaks Down for Agents in Production
AI governance designed for static models cannot govern autonomous agents that reason dynamically and act at machine speed. The evidence from every major analyst, standards body, and tech platform converges on one conclusion: governance must move inside the system.
Accountable Autonomy: Oversight for AI Agents
The debate around human oversight is often framed as a false binary: humans review every decision or AI operates autonomously. Effective oversight is about having the right controls at the right moments with clear accountability. This is accountable autonomy.
AI Agent Audit Trails: Actions, Evidence & Replay
Learn how to create audit trails for AI agent actions, replay decisions, verify policy and approval evidence, and prove record integrity.
AI Governance Bottleneck: Why Agent Adoption Stalls
Enterprise AI agent adoption is constrained not by technical capability but by governance capacity. Organizations can build AI agents faster than they can approve, monitor, and audit them. Closing this governance gap requires treating governance as enabling infrastructure.
Shadow AI: The Hidden Compliance Risk in Your Organization
How unauthorized AI tools create compliance blind spots under the EU AI Act. Learn to identify, inventory, and govern shadow AI before regulators find it first.
AI Agent Compliance Guide: EU AI Act Requirements
Classify AI agent systems, map provider and deployer duties, and document human oversight, logging, risk controls, monitoring, and audit evidence.