NIST AI Risk Management Framework (AI RMF) v1.0
- ClassificationCategoryArtificial IntelligenceDomainRisk ManagementFramework FamilyNIST Frameworks
- Regulatory ContextTypeStandardLegal InstrumentFrameworkSectorCross-SectorIndustryCross-Industry
- Region / PublisherRegionNorth AmericaRegion DetailUnited StatesPublisherNational Institute of Standards and Technology (NIST)
- VersioningVersionNIST AI RMF v1.0Effective DateJanuary 26, 2023Issue DateJanuary 26, 2023
- AdoptionAdoption ModelRisk ManagementImplementation ComplexityModerate
- Official ReferenceOpen Link in New TabSource
License included / downloadable: Yes
The NIST AI Risk Management Framework is publicly available through official NIST publications.
Framework text is licensed by its publisher and is included only where stated above.
Overview
NIST AI Risk Management Framework (AI RMF) v1.0 is a risk management framework that assists organizations in identifying, assessing, and managing risks associated with the design, development, deployment, and use of artificial intelligence (AI) systems. Its primary purpose is to promote trustworthy and responsible AI while addressing cybersecurity, privacy, and broader risk considerations across organizational contexts.
Developed and published by the National Institute of Standards and Technology (NIST), the AI RMF is intended for organizations of all sizes and sectors involved with AI technologies. The framework is used by risk managers, technology leaders, compliance teams, and developers to govern AI risks alongside established frameworks like NIST CSF and NIST SP 800-53. It covers issues such as transparency, accountability, data protection, and the integration of security controls within AI workflows.
Organizations typically implement the NIST AI RMF by conducting risk assessments, instituting internal controls for AI processes, and aligning AI governance with existing cybersecurity, risk, and compliance programs. The framework supports organizations in developing risk management practices for AI, ensuring operational resilience, and meeting evolving regulatory and industry expectations.
Why it Matters
The NIST AI Risk Management Framework (AI RMF) helps organizations responsibly manage AI risks and build trust in AI technologies across operations.
Key benefits include:
- Strengthen AI risk governance
Improve the oversight of AI development and deployment through structured risk identification, assessment, and mitigation processes.
- Enhance regulatory preparedness
Support compliance with emerging AI-related laws and standards by aligning risk management practices with recognized national guidance.
- Promote operational resilience
Enable organizations to maintain critical functions by anticipating, addressing, and recovering from AI-driven incidents or disruptions.
- Improve transparency and accountability
Foster clear documentation and tracking of AI decision-making processes, supporting stakeholder trust and external audit requirements.
- Protect sensitive data and systems
Reduce the risk of privacy breaches and data misuse by integrating privacy-enhancing measures and security controls within AI workflows.
How it Works
The NIST AI Risk Management Framework (AI RMF) v1.0 is organized around a Core of interrelated functions—Map, Measure, Manage, and Govern—plus Implementation Tiers and Profiles that help tailor adoption to organizational needs. The Core breaks outcomes into categories and subcategories that map to informative references and existing control catalogs (for example, NIST SP 800-53), providing a lifecycle-oriented structure for AI risk management and governance.
Organizations apply the AI RMF by inventorying AI systems, conducting risk assessments, and mapping identified risks to security controls and governance policies across the model lifecycle. Teams establish roles and oversight, implement technical and procedural safeguards, perform model testing and monitoring, and run compliance assessments and incident response exercises to manage residual risk and demonstrate adherence to regulatory requirements.
Within SmartSuite, teams can operationalize the AI RMF by importing control libraries, building risk registers, and linking AI assets to profiles and policies. SmartSuite supports evidence collection, compliance tracking, remediation workflows, audit readiness, and reporting dashboards to monitor security practices, track progress against risk management objectives, and produce regulator-ready reports.
Key Elements
- Governance and Organizational Oversight
Specifies roles, responsibilities, and decision-making structures for managing AI-related risks organization-wide.
- Risk Management Processes
Outlines systematic procedures for identifying, assessing, and mitigating risks across the AI system lifecycle.
- Mapping AI System Functions
Describes mechanisms for documenting, classifying, and contextualizing AI system capabilities and intended uses.
- Measuring and Monitoring Controls
Establishes methods for evaluating risk posture, system performance, and compliance with security and privacy requirements.
- Risk Response and Remediation
Defines approaches for addressing identified risks and ensuring continuous improvement in AI risk management.
- Documentation and Transparency Practices
Organizes requirements for maintaining records, traceability, and clear communication regarding AI system design and operation.
Framework Scope
NIST AI Risk Management Framework (AI RMF) v1.0 supports enterprises developing, deploying, or integrating artificial intelligence technologies across business processes and digital ecosystems. It governs AI models, algorithms, and data processing environments, and is employed to manage evolving AI-related risks, improve risk oversight, and support organizational compliance and data protection initiatives.
Framework Objectives
NIST AI Risk Management Framework (AI RMF) provides a structured basis for managing AI-related risks and ensuring responsible AI practices.
Strengthen cybersecurity governance across AI system life cycles
Enhance risk management processes specific to artificial intelligence technologies
Support compliance with emerging regulatory and industry standards
Improve data protection and privacy within AI workflows
Promote transparency and accountability in AI system design and use
Enable operational resilience by integrating effective security controls NIST AI Risk Management Framework complements the EU AI Act, NIST Cybersecurity Framework, and ISO/IEC 27001 by aligning AI-specific risk practices with established security and privacy controls. Organizations implement it for regulatory compliance, governance and assurance, vendor assessment, and operational risk reduction in AI development and deployment.
Organizations map AI RMF controls to established regulatory, privacy, and security standards to simplify governance, ensure legal alignment, and integrate AI risk management into enterprise compliance programs.
Mapped frameworks include:
EU AI Act
ISO/IEC 27001
ISO/IEC 27701
ISO/IEC 42001
NIST Cybersecurity Framework
NIST Privacy Framework
NIST Special Publication 800-53
OECD AI Principles
Framework in Context
NIST AI Risk Management Framework complements the EU AI Act, NIST Cybersecurity Framework, and ISO/IEC 27001 by aligning AI-specific risk practices with established security and privacy controls. Organizations implement it for regulatory compliance, governance and assurance, vendor assessment, and operational risk reduction in AI development and deployment.
How SmartSuite Supports NIST AI RMF AI 100-1 v1.0
SmartSuite provides the system for managing controls, evidence, mappings, assessments, and reporting.
Centralize controls, evidence, and audit workflows to stay continuously SOC 2–ready.
AI Risk Functions and Ownership
Organize AI risk work by AI RMF functions with clear ownership and cadence.
Use Case and Impact Mapping
Document intended use, affected stakeholders, and impact considerations per use case.
Measurement and Evaluation Evidence
Capture testing results, validation metrics, and monitoring outputs over time.
Mitigation, Approval, and Remediation Tracking
Track mitigations, approvals, residual risk acceptance, and remediation timelines.
Vendor and Model Provider Oversight
Manage third-party AI due diligence, controls, and evidence for sourced models.
AI Risk Program Reporting and Readiness
Report AI risk posture, gaps, and readiness across systems and business areas.
Related frameworks
ISO/IEC 27001:2022 is an international ISMS standard that helps organizations manage information security risks and protect data.
ISO/IEC 27701 extends ISO/IEC 27001 to help organizations manage privacy and protect personally identifiable information.
ISO/IEC 42001 is an AI management system standard for managing AI risk, ethics, security, and regulatory compliance.
NIST Cybersecurity Framework (CSF) v2.0 is a risk-based framework that helps organizations manage and reduce cybersecurity risks.
Frequently Asked Questions For NIST AI Risk Management Framework (AI RMF)
The NIST AI RMF helps organizations identify, assess, and manage the risks associated with the design, development, deployment, and use of artificial intelligence systems. It provides structured guidance for fostering trustworthy, accountable, and secure AI within different organizational and regulatory contexts.
The NIST AI RMF is a voluntary guidance framework and does not currently have a formal certification process or mandate. Organizations may choose to implement the AI RMF to align with industry best practices, meet regulatory expectations, or support internal risk management objectives.
The AI RMF applies to any organization designing, developing, deploying, or using AI systems, regardless of size or sector. Its guidance is relevant to risk managers, compliance teams, developers, and executives involved in AI governance and operational risk.
Core concepts within the framework include the Map, Measure, Manage, and Govern functions, which structure risk management activities across the AI lifecycle. Artifacts may include risk assessments, control mappings, inventories of AI systems, governance policies, and compliance documentation.
Implementation often begins with an inventory of AI systems and related assets, followed by structured risk assessment and mapping of risks to controls and governance policies. Organizations establish roles, oversight mechanisms, and ongoing monitoring practices to manage residual risk.
The AI RMF is designed to complement existing risk management and cybersecurity frameworks, such as the NIST Cybersecurity Framework and NIST SP 800-53. It references these frameworks when aligning AI risk controls and governance with broader organizational security and compliance strategies.
Ongoing requirements include continuous risk monitoring, periodic reassessment of AI systems and controls, routine compliance checks, incident response planning, and regular updates to documentation. Teams must demonstrate due diligence in managing AI-related risks over time.
SmartSuite supports NIST AI RMF by enabling organizations to track risks, manage AI-specific controls, and link assets to policies and governance profiles. It facilitates evidence collection, compliance monitoring, remediation management, and audit readiness with configurable dashboards and reporting tools, ensuring organizations can meet regulatory and framework requirements efficiently.
Manage controls, risks, evidence, and audits in one platform designed for modern governance, risk, and compliance.