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NIST AI RMF Checklist

Assess your AI risk management maturity

GOVERN - Governance & Culture

Do you have an established AI governance structure (roles, decision-making processes, accountability)?

Comprehensive governance in place Basic governance exists No formal governance

Have you defined risk tolerance levels and acceptability thresholds for AI systems?

Yes, formally defined and documented Informally exists Not defined

Do you have a process for managing risks from third-party AI components and services?

Systematic third-party risk management Basic vendor assessment exists No third-party management

Do you have documented ethical guidelines and values for AI development and use?

Comprehensive ethical framework Basic ethical guidelines exist No formal ethical guidelines

Are there clear accountability mechanisms for AI decisions and outputs?

Clear accountability chains exist Partially defined Unclear or undefined

Is there a continuous improvement process for AI governance and risk management?

Systematic continuous improvement Occasional reviews No improvement process

MAP - Context Mapping

Have you mapped the AI system's operational context (stakeholders, use cases, impacts)?

Comprehensive context mapping Basic mapping exists No context mapping

Have you identified all stakeholders (users, affected individuals, regulators)?

All stakeholders identified Main stakeholders identified Not identified

Have you mapped the complete AI system lifecycle (design, development, deployment, monitoring, retirement)?

Full lifecycle documented Partial lifecycle mapping No lifecycle mapping

Have you conducted impact assessments (identifying positive and negative impacts)?

Comprehensive impact assessment done Basic impact assessment No impact assessment

Have you mapped applicable legal and regulatory requirements?

Comprehensive legal mapping Main regulations identified No legal mapping

MEASURE - Measurement & Assessment

Do you have an established methodology for measuring AI risks?

Systematic risk measurement Ad-hoc measurements No methodology

Do you continuously measure AI system performance (accuracy, precision, recall, F1)?

Continuous performance monitoring Periodic measurements No performance measurement

Do you measure fairness and bias metrics across different groups?

Comprehensive fairness/bias monitoring Basic bias measurements No fairness/bias measurement

Do you regularly test AI system security and robustness (e.g., adversarial testing)?

Regular security testing Occasional testing No security testing

Do you measure the AI system's explainability and transparency levels?

Explainability regularly measured Basic assessment performed Not measured

Is there continuous monitoring for AI operations (e.g., drift detection, anomaly detection)?

Automated continuous monitoring Manual periodic checks No monitoring

MANAGE - Risk Management Execution

Do you have documented risk mitigation plans for identified AI risks?

Comprehensive mitigation plans Basic mitigation plans No plans

Do you have an AI-specific incident response plan and team?

Dedicated AI IR plan and team Integrated into general IR No AI IR

Is there a formal change management process for AI system modifications?

Formal change management exists Informal process exists No change management

Do you regularly document and report AI risks and mitigation steps?

Systematic documentation and reporting Occasional documentation No documentation

Are adequate resources (budget, people, tools) allocated to AI risk management?

Adequate resources allocated Limited resources Insufficient resources

Your AI Security Assessment

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Are your AI systems trustworthy and secure?

Take our 3-Minute NIST AI RMF Checklist! The NIST AI Risk Management Framework (RMF) is key to building trustworthy AI. This checklist assesses your alignment with its “Govern, Map, Measure, Manage” principles, from transparency to bias management. Complete it in just 3 minutes to get an instant evaluation of your AI risk posture!

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