AI Governance Controls
Choose a control domain to see what your team needs to implement. Each control includes regulatory mappings, maturity levels, and implementation guidance.
See how controls form an AI governance framework. You can also compare tools organized by the same control domains.
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Human Oversight
Review gates, approval workflows, and override mechanisms for AI decisions.
7 controls
AGTAgentic AI
Goal constraints, action boundaries, and escalation paths for autonomous AI agents.
30 controls
SECSecurity
Defenses against crafted inputs that trick AI into misbehaving, including prompt injection, plus controls on who can use each model.
7 controls
ALCAudit & Logging
Tamper-proof records of AI decisions, inputs, outputs, and which model version produced them.
5 controls
CHMChange Management
Model release governance, version rollback, and change approval workflows.
5 controls
DGCData Governance
Training data provenance, privacy controls, and data retention policies.
6 controls
MONMonitoring & Drift
Catching AI accuracy that slips over time (drift), alerts on unusual behavior, and operational dashboards.
6 controls
SAFSafety & Reliability
Safe fallbacks when AI fails, output checks, and reliable behavior when someone tries to trick the system.
6 controls
IRCIncident Response
Containment, investigation, and remediation procedures for AI system failures.
6 controls
PRCProcurement
Third-party AI vendor due diligence, contractual obligations, and offboarding.
18 controls
CMPRegulatory Compliance
Multi-jurisdiction regulatory mapping, standards monitoring, and compliance architecture for AI systems.
10 controls
BRDBoard & Executive Governance
Board education, committee charters, executive reporting, risk appetite, and enterprise-wide AI governance program design.
11 controls
MGVModel & Program Governance
Model lifecycle policy, intake and approval workflows, evaluation frameworks, and program-level AI governance maturity.
10 controls
SCTSector-Specific & Emerging
Healthcare, insurance, critical infrastructure, national security, and emerging-use-case controls not covered by domain-general frameworks.
9 controls
8 controls matching filters
Human Oversight
1 controlAgentic AI
2 controlsHuman Oversight Classification Rationale Log
Document why each AI agent action requires human-in-the-loop (approval first) or human-on-the-loop (monitoring) oversight. Retain an auditable record of the reasoning behind those choices.
Agent Ownership and Accountability Register
Keep a register that names an accountable person for every deployed AI agent. Record who owns its outcomes, who sponsors it at executive level, and what happens when either person leaves.
Security
1 controlChange Management
1 controlIncident Response
3 controlsAI Incident Classification
Classify AI incidents by type and severity. Use the categories to set response urgency and notification requirements.
AI Post-Incident Review
Conduct a structured review after every significant AI incident to identify root causes, contributing factors, and systemic improvements.
AI Incident Log and Tracking
Maintain a centralized, structured log of all AI incidents, near-misses, and governance concerns, accessible to the AI governance function.