NIST AI RMF 1.1 (Risk Management Framework)
📅 Published: 2026-04-18 | ⏱️ Reading Time: ~5 minutes
Overview
NIST AI RMF (Risk Management Framework) is the AI risk management framework published by the U.S. National Institute of Standards and Technology (NIST) in 2023.
Key Features:
- Voluntary Compliance — No legal enforcement
- Federal Procurement Requirement: NIST AI RMF compliance mandatory for U.S. government contracts (EO 14110)
- International Compatibility: Interoperable with ISO/IEC 42001
Version History:
- v1.0 (Jan 2023): Initial release
- v1.1 (Dec 2024): Added Generative AI section, enhanced transparency
4 Functions — GOVERN, MAP, MEASURE, MANAGE
1. GOVERN
Purpose: Establish AI system governance policies, culture, and accountability
Core Subcategories:
- GOVERN-1.1: Establish AI risk management strategy
- GOVERN-1.2: Clarify accountability (AI system owners)
- GOVERN-1.3: Integrate legal, regulatory, and ethical considerations
- GOVERN-1.4: Foster organization-wide AI risk culture
AIDLC Mapping: Governance Framework — 3-layer governance model
2. MAP
Purpose: Understand AI system context, identify risks
Core Subcategories:
- MAP-1.1: Understand business context (use cases, stakeholders)
- MAP-1.2: Define AI system scope (inputs, outputs, dependencies)
- MAP-2.1: Assess data quality
- MAP-3.1: Identify risks (bias, privacy, security)
- MAP-5.1: Impact assessment
AIDLC Mapping: Inception → Requirements Analysis, Reverse Engineering
3. MEASURE
Purpose: Measure AI system performance, trustworthiness, fairness
Core Subcategories:
- MEASURE-1.1: Define performance metrics (accuracy, F1, AUC)
- MEASURE-2.1: Assess explainability
- MEASURE-2.2: Bias testing (demographic parity, equalized odds)
- MEASURE-2.3: Robustness testing (adversarial robustness)
- MEASURE-3.1: Privacy impact assessment
AIDLC Mapping: Construction → Build & Test, Harness Engineering Quality Gates
4. MANAGE
Purpose: AI risk response, monitoring, continuous improvement
Core Subcategories:
- MANAGE-1.1: Execute risk mitigation strategies
- MANAGE-2.1: Incident response planning
- MANAGE-3.1: Continuous monitoring
- MANAGE-4.1: Feedback loop (risk reassessment)
AIDLC Mapping: Operations → Post-market monitoring, incident response
NIST AI RMF 1.0 → 1.1 Major Changes
| Item | v1.0 (Jan 2023) | v1.1 (Dec 2024) |
|---|---|---|
| Generative AI | Brief mention | Dedicated section added (Appendix B) |
| Transparency | MEASURE-2.1 | Enhanced (Model Card, Data Sheet examples) |
| Red Teaming | - | Added MEASURE-2.3 (adversarial testing) |
| Supply Chain | GOVERN-1.5 | Expanded (open-source model risks) |
U.S. Federal Procurement Requirements (EO 14110)
Executive Order 14110 (Oct 30, 2023): "Safe, Secure, and Trustworthy AI"
Key Points:
- Federal agencies must comply with NIST AI RMF when deploying AI
- Models exceeding 10^26 FLOP must report to government
- Federal procurement contracts must include AI risk management clauses
AIDLC Response: NIST AI RMF mapping mandatory for U.S. federal contract projects
AIDLC Integration Examples
Inception Stage: GOVERN + MAP
# .aidlc/compliance/nist-map.yaml
project: federal-contract-ai-tool
assessment_date: 2026-04-18
# GOVERN-1.1: AI Risk Management Strategy
governance:
strategy: "Federal contract-compliant AI code generation tool"
responsible_party: "AI Governance Team"
# MAP-1.1: Business Context
business_context:
use_case: "Federal agency backend service code generation"
stakeholders:
- "Federal procurement officers"
- "Development team"
- "Security team"
# MAP-3.1: Risk Identification
identified_risks:
- risk_id: RISK-001
category: "Security"
description: "Vulnerabilities in generated code"
mitigation: "Automated SAST scanning"
- risk_id: RISK-002
category: "Privacy"
description: "PII exposure"
mitigation: "Guardrails filtering"
Construction Stage: MEASURE
# .aidlc/harness/nist-measure-gates.yaml
quality_gates:
# MEASURE-1.1: Performance Metrics
- gate: performance_metrics
enabled: true
metrics:
code_coverage: ">= 80%"
duplication: "<= 3%"
# MEASURE-2.2: Bias Testing
- gate: bias_test
enabled: true
tests:
- "demographic_parity_check"
- "equalized_odds_check"
# MEASURE-2.3: Robustness Testing
- gate: adversarial_robustness
enabled: true
tools:
- "bandit" # SAST
- "semgrep"
Operations Stage: MANAGE
# .aidlc/monitoring/nist-manage.yaml
continuous_monitoring:
# MANAGE-3.1: Continuous Monitoring
metrics:
- name: "error_rate"
target: "< 1%"
alert_threshold: 0.95
- name: "bias_score"
target: "< 0.05"
alert_threshold: 0.04
# MANAGE-4.1: Feedback Loop
feedback_loop:
frequency: "monthly"
action: "Risk reassessment and mitigation strategy update"
References
Official Documents:
Related Documentation: