NIST AI Risk Management Framework (AI RMF) v1.0
SmartSuite provides the system for managing controls, evidence, mappings, assessments, and reporting. Framework text may require a separate license unless explicitly provided.
Overview
NIST AI RiskManagement Framework (AI RMF) v1.0 is a risk management frameworkthat assists organizations in identifying, assessing, and managingrisks associated with the design, development, deployment, and use ofartificial intelligence (AI) systems. Its primary purpose is topromote trustworthy and responsible AI while addressingcybersecurity, privacy, and broader risk considerations acrossorganizational contexts.
Developed andpublished by the National Institute of Standards and Technology(NIST), the AI RMF is intended for organizations of all sizes andsectors involved with AI technologies. The framework is used by riskmanagers, technology leaders, compliance teams, and developers togovern AI risks alongside established frameworks like NIST CSF andNIST SP 800-53. It covers issues such as transparency,accountability, data protection, and the integration of securitycontrols within AI workflows.
Organizationstypically implement the NIST AI RMF by conducting risk assessments,instituting internal controls for AI processes, and aligning AIgovernance with existing cybersecurity, risk, and complianceprograms. The framework supports organizations in developing robustrisk management practices for AI, ensuring operational resilience,and meeting evolving regulatory and industry expectations.
Why it Matters
The NIST AI RiskManagement Framework (AI RMF) helps organizations responsibly manageAI risks and build trust in AI technologies across operations.
Key benefitsinclude:
• Strengthen AI risk governance
Improve theoversight of AI development and deployment through structured riskidentification, assessment, and mitigation processes.
• Enhance regulatory preparedness
Supportcompliance with emerging AI-related laws and standards by aligningrisk management practices with recognized national guidance.
• Promote operational resilience
Enableorganizations to maintain critical functions by anticipating,addressing, and recovering from AI-driven incidents or disruptions.
• Improve transparency and accountability
Foster cleardocumentation and tracking of AI decision-making processes,supporting stakeholder trust and external audit requirements.
• Protect sensitive data and systems
Reduce the riskof privacy breaches and data misuse by integrating privacy-enhancingmeasures and robust security controls within AI workflows.
How it Works
The NIST AI RiskManagement Framework (AI RMF) v1.0 is organized around a Core ofinterrelated functions—Map, Measure, Manage, and Govern—plusImplementation Tiers and Profiles that help tailor adoption toorganizational needs. The Core breaks outcomes into categories andsubcategories that map to informative references and existing controlcatalogs (for example, NIST SP 800-53), providing alifecycle-oriented structure for AI risk management and governance.
Organizationsapply the AI RMF by inventorying AI systems, conducting riskassessments, and mapping identified risks to security controls andgovernance policies across the model lifecycle. Teams establish rolesand oversight, implement technical and procedural safeguards, performmodel testing and monitoring, and run compliance assessments andincident response exercises to manage residual risk and demonstrateadherence to regulatory requirements.
WithinSmartSuite, teams can operationalize the AI RMF by importing controllibraries, building risk registers, and linking AI assets to profilesand policies. SmartSuite supports evidence collection, compliancetracking, remediation workflows, audit readiness, and reportingdashboards to monitor security practices, track progress against riskmanagement objectives, and produce regulator-ready reports.
Key Elements
• Governance and Organizational Oversight
Specifies roles,responsibilities, and decision-making structures for managingAI-related risks organization-wide.
• Risk Management Processes
Outlinessystematic procedures for identifying, assessing, and mitigatingrisks across the AI system lifecycle.
• Mapping AI System Functions
Describesmechanisms for documenting, classifying, and contextualizing AIsystem capabilities and intended uses.
• Measuring and Monitoring Controls
Establishesmethods for evaluating risk posture, system performance, andcompliance with security and privacy requirements.
• Risk Response and Remediation
Definesapproaches for addressing identified risks and ensuring continuousimprovement in AI risk management.
• Documentation and Transparency Practices
Organizesrequirements for maintaining records, traceability, and clearcommunication regarding AI system design and operation.
Framework Scope
NIST AI RiskManagement Framework (AI RMF) v1.0 supports enterprises developing,deploying, or integrating artificial intelligence technologies acrossbusiness processes and digital ecosystems. It governs AI models,algorithms, and data processing environments, and is employed tomanage evolving AI-related risks, improve risk oversight, and supportorganizational compliance and data protection initiatives.
Framework Objectives
NIST AI RiskManagement Framework (AI RMF) provides a structured basis formanaging AI-related risks and ensuring responsible AI practices.
• Strengthen cybersecurity governance across AI system life cycles
• Enhance risk management processes specific to artificialintelligence technologies
• Support compliance with emerging regulatory and industrystandards
• Improve data protection and privacy within AI workflows
• Promote transparency and accountability in AI system design anduse
• Enable operational resilience by integrating effective securitycontrols NIST AI Risk Management Framework complements the EU AI Act,NIST Cybersecurity Framework, and ISO/IEC 27001 by aligningAI-specific risk practices with established security and privacycontrols. Organizations implement it for regulatory compliance,governance and assurance, vendor assessment, and operational riskreduction in AI development and deployment.
Organizationsmap AI RMF controls to established regulatory, privacy, and securitystandards to streamline governance, ensure legal alignment, andintegrate AI risk management into enterprise compliance programs.
Mappedframeworks include:
EU AI Act
ISO/IEC 27001
ISO/IEC 27701
ISO/IEC 42001
NISTCybersecurity Framework
NIST PrivacyFramework
NIST SpecialPublication 800-53
OECD AIPrinciples
- ClassicifationCategoryArtificial 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.
How SmartSuite Supports NIST AI RMF AI 100-1 v1.0
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.
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