NIST AI Risk Management Framework (AI RMF) v1.0

Why it Matters

The NIST AI Risk Management Framework (AI RMF) helps organizationsresponsibly manage AI risks and build trust in AI technologies acrossoperations.

Key benefits include:

• 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 Risk Management Framework (AI RMF) v1.0 is organizedaround a Core of interrelated functions—Map, Measure, Manage, andGovern—plus Implementation Tiers and Profiles that help tailoradoption to organizational needs. The Core breaks outcomes intocategories and subcategories that map to informative references andexisting control catalogs (for example, NIST SP 800-53), providing alifecycle-oriented structure for AI risk management and governance.

Organizations apply the AI RMF by inventorying AI systems, conductingrisk assessments, and mapping identified risks to security controlsand governance policies across the model lifecycle. Teams establishroles and oversight, implement technical and procedural safeguards,perform model testing and monitoring, and run compliance assessmentsand incident response exercises to manage residual risk anddemonstrate adherence to regulatory requirements.

Within SmartSuite, teams can operationalize the AI RMF by importingcontrol libraries, building risk registers, and linking AI assets toprofiles and policies. SmartSuite supports evidence collection,compliance tracking, remediation workflows, audit readiness, andreporting dashboards to monitor security practices, track progressagainst risk management objectives, and produce regulator-readyreports.

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 Risk Management Framework (AI RMF) v1.0 supports enterprisesdeveloping, deploying, or integrating artificial intelligencetechnologies across business processes and digital ecosystems. Itgoverns AI models, algorithms, and data processing environments, andis employed to manage evolving AI-related risks, improve riskoversight, and support organizational compliance and data protectioninitiatives.

Framework Objectives

NIST AI Risk Management Framework (AI RMF) provides a structuredbasis for managing AI-related risks and ensuring responsible AIpractices.

Strengthen cybersecurity governance across AI system life cycles

Enhance risk management processes specific to artificial intelligencetechnologies

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 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.

Organizations map AI RMF controls to established regulatory, privacy,and security standards to streamline governance, ensure legalalignment, and integrate AI risk management into enterprisecompliance 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 RiskManagement Framework complements the EU AI Act, NIST CybersecurityFramework, and ISO/IEC 27001 by aligning AI-specific risk practiceswith established security and privacy controls. Organizationsimplement it for regulatory compliance, governance and assurance,vendor assessment, and operational risk reduction in AI developmentand deployment.