Regulatory Standard
NIST AI RMF
The NIST AI Risk Management Framework provides a voluntary, principles-based approach to managing AI risk through four functions: Govern, Map, Measure, and Manage. These COMPEL articles align with the RMF playbook and help operationalize each function.
168 articles aligned to NIST AI RMF.
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Calibrate (20)
- M1.3
AI Supply Chain Governance: The Missing Domain
AI Governance Structure · Foundation - M1.3
Artifact Template: Experiment Brief
AI Governance Structure · Applied - M1.3
Case Study 3: Dutch Toeslagenaffaire — Counterfactual Failure and Externality Accounting
AI Governance Structure · Advanced - M1.3
Continuous Delivery and Governed Promotion
AI Governance Structure · Applied - M1.3
Control Performance Reports for AI Programs
AI Governance Structure · Advanced - M1.3
Designing an Evaluation Harness for Value
AI Governance Structure · Advanced - M1.3
Drift Detection and Value Erosion
AI Governance Structure · Advanced - M1.3
Enforcement, Penalties, and the Obligation-to-Control Crosswalk
AI Governance Structure · Foundation - M1.3
Governance Pillar Domains: Risk and Structure
AI Governance Structure · Foundation - M1.3
Lab 1: Write a Measurement Plan for an AI Feature
AI Governance Structure · Advanced - M1.3
Obligations on High-Risk AI Systems
AI Governance Structure · Foundation - M1.3
Offline Evaluation
AI Governance Structure · Applied - M1.3
Pipelines and Orchestration
AI Governance Structure · Applied - M1.3
Regulatory Documentation for Experiments
AI Governance Structure · Applied - M1.3
Template 1: Measurement Plan (11 Sections)
AI Governance Structure · Advanced - M1.3
Template 4: Value Realization Report (VRR)
AI Governance Structure · Advanced - M1.3
The AI Value Chain
AI Governance Structure · Advanced - M1.3
The Measurement Plan Artifact
AI Governance Structure · Advanced - M1.3
The Value Realization Report
AI Governance Structure · Advanced - M1.3
What an AI Experiment Is
AI Governance Structure · Applied
Organize (1)
Model (15)
- M1.2
Multi-Rater Assessment and Evidence Rules
AI Use Case Management · Foundation - M1.2
Output Structuring and Constrained Decoding
AI Use Case Management · Applied - M3.3
Measuring AI Safety: Content, Jailbreak, and Grounding Metrics
Integration Architecture · Advanced - M3.3
Measuring AI Security: Injection Resistance, Leakage, and Integrity Metrics
Integration Architecture · Advanced - M3.4
Agentic AI Risk Taxonomy and Enterprise Risk Framework Extension
ML Operations and Deployment · Advanced - M3.4
Enterprise Multi-Framework Compliance Strategy
Regulatory Compliance · Advanced - M3.4
Measuring AI Responsibility: Bias, Fairness, and Explainability Metrics
Regulatory Compliance · Advanced - M3.4
Proactive Regulatory Engagement
Regulatory Compliance · Advanced - M4.3
Board Compliance Reporting Across Jurisdictions
Regulatory Compliance · Strategic - M4.3
Cross-Organizational Governance Architecture Design
Regulatory Compliance · Strategic - M4.3
Enterprise Policy Lifecycle Management and Version Control
Regulatory Compliance · Strategic - M4.3
ISO 42001 Alignment and AI Management System Certification
Regulatory Compliance · Strategic - M4.3
Measuring AI Compliance: Control Coverage, Conformity Gaps, and Audit Readiness
Regulatory Compliance · Strategic - M4.3
NIST AI RMF Implementation at Enterprise Scale
Regulatory Compliance · Strategic - M4.3
The AITL Lead as Governance Harmonization Authority
Regulatory Compliance · Strategic
Evaluate (1)
Learn (4)
- M4.5
Industry Standards for Agentic AI: ISO, NIST, and Emerging Frameworks
ML Operations and Deployment · Strategic - M4.5
Methodology Benchmarking and Comparative Analysis
Regulatory Compliance · Strategic - M4.5
Standards Body Engagement — ISO, IEEE, NIST, and Beyond
Regulatory Compliance · Strategic - M4.5
The AITL Lead as Industry Standards Architect
Regulatory Compliance · Strategic
Lifecycle-Wide (127)
- M1.1
Architecture Decision Records and Documentation
AI Strategy and Alignment · Advanced - M1.1
Architecture for Agentic Use Cases
AI Strategy and Alignment · Advanced - M1.1
Architecture Handoff and Operating Model
AI Strategy and Alignment · Advanced - M1.1
Architecture Runway: Building the AI Platform
AI Strategy and Alignment · Advanced - M1.1
Artifact Template: LLM Evaluation Harness Specification
AI Strategy and Alignment · Advanced - M1.1
Build vs. Buy vs. Integrate
AI Strategy and Alignment · Advanced - M1.1
Drift Monitoring, Incident Classification, and Sustainment
AI Strategy and Alignment · Applied - M1.1
Evaluation, Red-Teaming, and Monitoring
AI Strategy and Alignment · Foundation - M1.1
Hallucination, Grounding, and Output Integrity
AI Strategy and Alignment · Foundation - M1.1
Model, Prompt, and Index Registries
AI Strategy and Alignment · Advanced - M1.1
Prompt Architecture: Templates, Versioning, Injection Defense
AI Strategy and Alignment · Advanced - M1.1
Prompt Injection and Jailbreak Mitigation
AI Strategy and Alignment · Foundation - M1.1
Regulatory Obligations and Incident Response
AI Strategy and Alignment · Foundation - M1.1
Responsible-AI Architecture Patterns
AI Strategy and Alignment · Advanced - M1.1
Retrieval-Augmented Generation: When, Why, How Much
AI Strategy and Alignment · Advanced - M1.1
Security Architecture for AI Applications
AI Strategy and Alignment · Advanced - M1.1
SLO, SLI, and Incident Response for AI
AI Strategy and Alignment · Advanced - M1.1
The Enterprise AI Reference Architecture
AI Strategy and Alignment · Advanced - M1.1
The LLM Risk Surface
AI Strategy and Alignment · Foundation - M1.1
What Data Readiness Is (and What It Is Not)
AI Strategy and Alignment · Applied - M1.2
Architect in Evaluate and Learn Stages for Agentic Systems
AI Use Case Management · Advanced - M1.2
Calibrate: Strategic Inputs You Must Gather Before You Begin
AI Use Case Management · Foundation - M1.2
Case Study — Anthropic Computer Use as a Controlled-Rollout Architecture
AI Use Case Management · Advanced - M1.2
Case Study: The Dutch Toeslagenaffaire as a Readiness-Failure Case
AI Use Case Management · Foundation - M1.2
Creating the AI Operating Model Blueprint
AI Use Case Management · Foundation - M1.2
EU AI Act Articles 14, 52, and Conformity Assessment for Agentic Systems
AI Use Case Management · Advanced - M1.2
Mandatory Artifacts and Evidence Management Across the COMPEL Cycle
AI Use Case Management · Foundation - M1.2
Prompt Evaluation Harness
AI Use Case Management · Applied - M1.2
Prompt Lifecycle Governance
AI Use Case Management · Applied - M1.2
Template — Agent Governance Charter (AITE-ATS instantiable per-agent)
AI Use Case Management · Advanced - M1.2
Template 01: Prompt Registry Entry and Test Plan
AI Use Case Management · Applied - M1.2
The Benchmark Update Report
AI Use Case Management · Foundation - M1.2
The COMPEL Operating Model: Roles, RACI, and Decision Rights
AI Use Case Management · Foundation - M1.2
Transparency and Regulatory Obligations
AI Use Case Management · Applied - M1.4
AI Operating Model Blueprint Template
Integration Architecture · Applied - M1.4
Apprenticeships, Fellowships, and Career Lattices
Integration Architecture · Advanced - M1.4
Belonging and Equity in AI-Transformed Work
Integration Architecture · Advanced - M1.4
Compliance-Grade Literacy Evidence
Integration Architecture · Advanced - M1.4
Decision Rights, Accountability, and Separation of Duties
Integration Architecture · Applied - M1.4
Defining AI Literacy at Four Levels
ML Operations and Deployment · Advanced - M1.4
Delivery at Scale Across Platforms
Integration Architecture · Advanced - M1.4
Designing a Role-Specific Literacy Curriculum
Integration Architecture · Advanced - M1.4
Inclusive Hiring for AI Roles
Integration Architecture · Advanced - M1.4
Lab: Build a Decision-Rights Matrix for an AI Risk Escalation
Integration Architecture · Applied - M1.4
Literacy Program Sustainability Over Multi-Year Horizons
Integration Architecture · Advanced - M1.4
Measuring Literacy Outcomes Beyond Completion
Integration Architecture · Advanced - M1.4
The AI Talent Pipeline End-to-End
Integration Architecture · Advanced - M1.4
Third-Party AI: The Governance Challenge You Are Not Seeing
Integration Architecture · Foundation - M1.4
What an AI Operating Model Is
Integration Architecture · Applied - M1.5
The AI Governance Imperative
Regulatory Compliance · Foundation - M1.5
The Geopolitical Landscape of AI Governance
Regulatory Compliance · Foundation - M1.5
The Global AI Regulatory Landscape
Regulatory Compliance · Foundation - M1.5
The Regulatory Convergence: 10 Requirements Every Framework Shares
Regulatory Compliance · Foundation - M1.5
Understanding the EU AI Act: Foundations for Governance
Regulatory Compliance · Foundation - M1.6
Agentic Risk Taxonomy
Change Management Capability · Applied - M1.6
Autonomy Classification
Change Management Capability · Applied - M1.6
Kill-Switch, Containment, and Incident Response
Change Management Capability · Applied - M1.6
Regulatory Obligations for Agentic Systems
Change Management Capability · Applied - M1.6
Template — Agent Governance Charter
Change Management Capability · Applied - M1.6
What Agentic AI Is
Change Management Capability · Applied - M1.8
Adversarial Attacks on AI Systems: Detection and Defense
AI Use Case Management · Foundation - M1.8
AI Security Foundations: Threat Models for Machine Learning Systems
AI Use Case Management · Foundation - M1.8
AI TRiSM: Trust, Risk, and Security Management as a Discipline
AI Use Case Management · Foundation - M1.8
Compliance Mappings: SOC 2, ISO 27001, and HIPAA for AI Workloads
AI Use Case Management · Foundation - M1.8
Data Poisoning: Training-Time Attacks and Mitigation Strategies
AI Use Case Management · Foundation - M1.8
Encryption in AI: At Rest, In Transit, and Confidential Computing
AI Use Case Management · Foundation - M1.8
Incident Response Playbooks for AI Security Events
AI Use Case Management · Foundation - M1.8
Logging, Auditing, and SIEM Integration for AI Systems
AI Use Case Management · Foundation - M1.8
Model Theft and Intellectual Property Protection in AI
AI Use Case Management · Foundation - M1.8
Network Isolation Patterns for AI Workloads: VPC, Service Mesh, Private Endpoints
AI Use Case Management · Foundation - M1.8
Red Teaming AI Systems: Methodologies, Cadence, and Playbooks
AI Use Case Management · Foundation - M1.8
Secure Model Serving: Authentication, Authorization, and Rate Limiting
AI Use Case Management · Foundation - M1.8
Supply-Chain Security for ML Dependencies and Model Weights
AI Use Case Management · Foundation - M1.10
AI Bill of Materials — MBOM and Model Lineage
AI Use Case Management · Foundation - M1.10
AI Procurement Policies — Buyer Power and Industry Standards
AI Use Case Management · Foundation - M1.10
Building a Tiered Vendor Risk Program for AI
AI Use Case Management · Foundation - M1.10
Continuous Monitoring of Vendor Model Behavior in Production
AI Use Case Management · Foundation - M1.10
Contracting Patterns for AI — SLAs, Indemnification, Data Use Restrictions
AI Use Case Management · Foundation - M1.10
Cross-Border Data Transfer and Sovereignty in AI Supply Chains
AI Use Case Management · Foundation - M1.10
Data Provenance — Tracing Training Data Sources Through the Pipeline
AI Use Case Management · Foundation - M1.10
Foundation Model Risk Assessment — Evaluating GPAI Providers
AI Use Case Management · Foundation - M1.10
Multi-Vendor AI Architecture — Avoiding Lock-in and Single Points of Failure
AI Use Case Management · Foundation - M1.10
Open Source Model Governance — License, Provenance, Quality
AI Use Case Management · Foundation - M1.10
Red Teaming Vendor Models Before Production Deployment
AI Use Case Management · Foundation - M1.10
The AI Supply Chain — From Foundation Models to Production Systems
AI Use Case Management · Foundation - M1.10
Third-Party API Risk — Hidden Dependencies on External AI Services
AI Use Case Management · Foundation - M1.10
Vendor Due Diligence Frameworks for AI Suppliers
AI Use Case Management · Foundation - M1.10
Vendor Incident Response and Notification Requirements
AI Use Case Management · Foundation - M1.11
Algorithmic Bias: Detection, Mitigation, and Continuous Monitoring
AI Use Case Management · Foundation - M1.11
Building an Ethics Review Process: From Use-Case Intake to Sign-Off
AI Use Case Management · Foundation - M1.11
Fairness in AI: Definitions, Metrics, and Implementation Tradeoffs
AI Use Case Management · Foundation - M1.11
Foundations of AI Ethics: Principles, Frameworks, and Practical Application
AI Use Case Management · Foundation - M1.11
Generative AI Ethics: Authorship, Consent, and Misuse Prevention
AI Use Case Management · Foundation - M1.11
Human Oversight in AI: Human-in-the-Loop, On-the-Loop, In-Command
AI Use Case Management · Foundation - M1.11
Measuring Ethics Maturity: Indicators, Audits, and Reporting
AI Use Case Management · Foundation - M1.11
Privacy-Preserving AI: Differential Privacy, Federated Learning, Synthetic Data
AI Use Case Management · Foundation - M1.11
Transparency Standards: Model Cards, Datasheets, and System Cards
AI Use Case Management · Foundation - M1.21
Risk Heat Maps for AI Programs
AI Use Case Management · Foundation - M1.23
AI Glossary: Building Shared Vocabulary in Your Org
AI Use Case Management · Foundation - M1.25
AI Maturity Self-Assessment Tools
AI Use Case Management · Foundation - M1.26
External Communications: AI Transparency to Customers
AI Use Case Management · Foundation - M1.27
ISO 42001 Certification Pathway
AI Use Case Management · Foundation - M1.27
NIST AI RMF Implementation Roadmap
AI Use Case Management · Foundation - M1.27
Regulatory Submission Preparation for High-Risk AI
AI Use Case Management · Foundation - M1.28
Evidence Collection for Compliance Audits
AI Use Case Management · Foundation - M2.6
EU AI Act Compliance for Practitioners
AI Use Case Management · Applied - M2.6
Implement Once, Comply with Many: The COMPEL Harmonization Approach
AI Use Case Management · Applied - M2.6
ISO 42001 Implementation Using COMPEL
AI Use Case Management · Applied - M2.6
Multi-Jurisdictional AI Compliance
AI Use Case Management · Applied - M2.6
NIST AI RMF Alignment with COMPEL Stages
AI Use Case Management · Applied - M2.6
Vendor AI Due Diligence: The Comprehensive Assessment
AI Use Case Management · Applied - M3.6
Measuring AI Reliability: SLOs, Drift, and Incident MTTR
AI Strategy and Alignment · Advanced - M3.7
AI Bill of Materials: Standards and Implementation
AI Use Case Management · Advanced - M4.1
Evaluating AI Governance Approaches — A Leader's Framework
AI Governance Structure · Strategic - M4.2
COMPEL and COBIT®: IT Governance Convergence
Regulatory Compliance · Strategic - M4.6
Strategic Third-Party AI Governance for Leaders
AI Governance Structure · Strategic - M9.1
AI Regulatory Harmonization Framework: One Control Library, Many Jurisdictions
AI Use Case Management · Advanced - M9.1
IEEE 7000 Ethical Design Implementation: A 10-Step Value-Based System Design Process
AI Use Case Management · Advanced - M9.1
ISO 42001 Operationalization Checklist: From Document Compliance to Operational Conformance
AI Use Case Management · Advanced - M9.1
NIST AI RMF to ISO 42001 Crosswalk: A Dual-Compliance Operating Map
AI Use Case Management · Advanced - M9.2
AI Governance RACI Matrix for Enterprises: Decision Rights Across 30 Activities and 12 Roles
AI Use Case Management · Advanced - M9.3
AI Agent Kill-Switch and Escalation Protocols: Architecture, Triggers, and Drills
AI Use Case Management · Strategic - M9.3
OWASP Top 10 for Agentic AI: Mitigation Playbook
AI Use Case Management · Strategic - M9.4
Enterprise AI Compliance Evidence Management: Always Audit-Ready
AI Use Case Management · Advanced - M9.4
Generative Engine Optimization (GEO) for AI Governance Brands
AI Use Case Management · Strategic - M9.4
Model Context Protocol Security Standards: A 12-Control Hardening Baseline
AI Use Case Management · Strategic - M9.4
Multi-Jurisdictional AI Governance Strategy: Global Baseline + Regional Overlays
AI Use Case Management · Strategic