Organizations implementing AI technologies must stay ahead of rapidly emerging governance and compliance requirements. Two of the most important frameworks are the NIST AI Risk Management Framework (NIST AI RMF) in the United States and the ISO/IEC 42001:2023 AI Management System standard used internationally. While each framework- serves a different regulatory environment, starting with the NIST AI Risk Management Framework provides a strong foundation that makes aligning with—and ultimately certifying against, ISO 42001 significantly easier.
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AI Governance and Compliance in 2025 and Beyond
Artificial intelligence (AI) adoption has accelerated dramatically, but formal governance standards are still maturing. Regulatory bodies continue to build structured, transparent rules for responsible AI use, prioritizing fairness, safety, and accountability over rapid policy rollout. As a result, organizations face a landscape where few mandatory AI regulations exist, making voluntary frameworks even more critical.
Two of the most important guidance documents available today come from the National Institute of Standards and Technology (NIST) and the International Organization for Standardization (ISO). Their respective frameworks—the NIST AI Risk Management Framework (AI RMF) and ISO/IEC 42001, AI Management System (AIMS) standard—serve as foundational tools for organizations seeking to implement responsible, secure, and compliant AI systems.
Preparing for AI governance and compliance in 2025 and beyond requires understanding:
- Whether your organization must, or should, adopt one or both frameworks
- How the NIST AI Risk Management Framework affects AI risk, trustworthiness, and operational controls
- How the ISO/IEC 42001:2023 standard defines requirements for an AI Management System (AIMS)
- Where the two frameworks align, enabling streamlined adoption and reduced implementation effort
- How assessments and certification can provide assurance to regulators, partners, and customers
Partnering with an experienced security and compliance advisor can help your organization build a scalable AI governance program and prepare for future regulatory requirements.
Who Needs to Comply with NIST AI Risk Management Framework or ISO/IEC 42001
As of October 2025, neither the NIST AI Risk Management Framework (AI RMF) nor ISO/IEC 42001 is legally required in the United States or internationally. However, there are compelling strategic and operational reasons for organizations to adopt one or both frameworks.
The NIST AI Risk Management Framework is especially relevant for U.S.-based organizations that collaborate with government agencies or partners who do. NIST standards often guide public-private partnerships and the broader network of strategic alliances surrounding them. Additionally, emerging federal, state, and local AI regulations are likely to draw heavily from NIST guidance, making early adoption a proactive compliance strategy.
Meanwhile, ISO/IEC 42001 should be on the radar for organizations operating internationally. ISO standards are widely recognized as global benchmarks for quality, safety, and governance. Similar to how NIST informs U.S. AI regulations, ISO 42001 is expected to influence legislation and best practices for AI management across multiple countries.
Adopting these frameworks not only supports regulatory readiness but also strengthens organizational credibility, risk management, and stakeholder trust in AI operations.
How the NIST AI Risk Management Framework Shapes AI Governance
The NIST AI Risk Management Framework (AI RMF) is designed to enable efficient, secure, and trustworthy AI operations by identifying, assessing, and mitigating the risks AI systems can pose. The framework provides a structured set of risk factors and defines core functions that organizations can use to govern AI responsibly.
Organizations can achieve trustworthy AI, according to NIST metrics, by implementing the best practices, policies, and procedures outlined in the AI RMF. A key feature of the framework is its Categories and Subcategories within the four core functions: Govern, Map, Measure, and Manage. These elements guide organizations in operationalizing AI governance and embedding it into day-to-day processes.
Adopting the NIST AI RMF not only strengthens internal AI governance but also lays the foundation for ISO/IEC 42001 compliance. By establishing top-down governance structures, clear communication channels, and operational visibility, organizations can more efficiently align with international AI management standards.
Overview of NIST AI Risk Management Framework Recommendations
NIST AI Risk Management Framework (AI RMF) draws on principles from other NIST guidance, including the Cybersecurity Framework (CSF) and the broader Risk Management Framework (RMF), to provide a structured approach to AI governance.
The framework is organized around four core functions, each with recommended Categories and Subcategories:
- Govern – Establish top-down policies and clear rules of order, implement accountability structures and training, promote diversity, equity, and inclusion, ensure communication and transparency, engage AI stakeholders, and manage third-party risks.
- Map – Define the context for AI systems, categorize AI use cases clearly, benchmark capabilities, goals, benefits, and costs, conduct detailed risk and benefit analyses (including third-party factors), and perform impact assessments.
- Measure – Apply standards for measuring AI system performance, conduct regular evaluations for safety, resilience, explainability, privacy, fairness, and environmental impact, monitor AI risks over time, and incorporate feedback into AI operations.
- Manage – Prioritize and respond to risks identified in the Map and Measure functions, maximize AI benefits while minimizing potential negative outcomes, manage third-party risks, and document and monitor ongoing AI activities.
Unlike some other frameworks, the Categories and Subcategories in NIST AI RMF are recommendations rather than mandatory requirements. Organizations can also leverage the NIST AI RMF Playbook, which provides practical methods for achieving these outcomes.
Partnering with a knowledgeable NIST AI RMF advisor can help organizations effectively implement these recommendations and ensure alignment with both internal governance and future regulatory expectations.
How ISO/IEC 42001:2023 Shapes AI Management
ISO/IEC 42001 a joint publication by the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC), focuses primarily on AI Management System (AIMS) governance rather than risk management alone. While its approach differs from the NIST AI Risk Management Framework (AI RMF), ISO 42001 also emphasizes risk considerations and broader AI security best practices to optimize AI system operations.
Most of ISO/IEC 42001 consists of mandatory clauses that define specific outcomes and controls organizations must implement for compliance. Clauses 1–3 cover scoping, definitions, and foundational concepts, while clauses 4–10 outline detailed operational requirements. Unlike the more flexible recommendations in NIST AI RMF, these clauses are prescriptive and must be followed closely.
Organizations that already implement best practices from the NIST AI RMF will find it easier to adopt ISO/IEC 42001 as the NIST framework provides a strong foundation of controls, governance structures, and operational visibility that align with ISO requirements.
Overview of ISO/IEC 42001 Requirements
The structure of ISO/IEC 42001 aligns with many other ISO standards, with central clauses outlining specific controls and required outcomes. These clauses are organized around pillars similar to the core functions of the NIST AI Risk Management Framework (AI RMF), enabling organizations to implement a structured AI Management System (AIMS).
The prescriptive clauses of ISO/IEC 42001 include:
Context of the Organization – Establish staff-wide understanding of organizational context for AIMS (4.1); identify AI needs and expectations of stakeholders (4.2); define the scope of AIMS operations (4.3); and clarify definitions for AIMS components (4.4).
Leadership – Ensure commitment from AI-relevant leaders and decision-makers (5.1); establish clear AI policies (5.2); define leadership roles and responsibilities (5.3).
Planning – Document and communicate plans for addressing AI risks and opportunities (6.1); achieve AIMS objectives (6.2); manage critical organizational changes (6.3).
Support – Provide resources, maintain staff competence (7.2), raise awareness (7.3), ensure effective communication (7.4), and manage documentation (7.5).
Operation – Implement policies and practices for planning and control (8.1); conduct AI risk assessments (8.2); apply risk treatments (8.3); perform system impact assessments (8.4).
Performance Evaluation – Standardize monitoring, measurement, analysis, and evaluation (9.1); conduct internal audits (9.2); and perform management reviews (9.3).
Improvement – Ensure continual improvement across AIMS (10.1) and implement formal corrective actions for nonconformities (10.2).
In addition, Annex A recontextualizes these clauses into a practical list of reference control objectives and actionable controls, helping organizations implement ISO 42001 effectively.
Partnering with an experienced ISO 42001 advisor can streamline adoption, ensuring your AI Management System meets compliance requirements while maximizing operational efficiency
Where NIST AI RMF and ISO/IEC 42001:2023 Overlap
The NIST AI Risk Management Framework (AI RMF) and ISO/IEC 42001:2023 share significant overlap, particularly in top-down governance and system-wide AI management, which are central to both frameworks. While NIST AI RMF emphasizes risk management, ISO 42001 addresses risks more selectively, for example in Clause 8 (AI Operations).
According to the Cloud Security Alliance (CSA), these convergence points also align with the European Union (EU) AI Act, underscoring their international importance. Key areas of alignment include:
- AI System Context – EU AI Act Article 1 expectations align with NIST AI RMF Govern Subcategories 1.1–1.4 and ISO 42001 Subclauses 4.1 and 6.2.
- AI Risk Management – EU AI Act Articles 9 and 27, covering AI risk and impact assessments for fundamental rights, correspond to NIST AI RMF Govern Subcategories 1.4–1.5 and ISO 42001 Subclauses 8.2–8.3.
- AI Incident Management – EU AI Act Article 73 on incident reporting aligns with NIST AI RMF Govern 4.3 and ISO 42001 Annex A Control 8.4.
- AI Communications – EU AI Act Article 17 on quality management maps to NIST AI RMF Govern 2.1, 4.2–4.3, and Map 1.3, and ISO 42001 Clause 7.4.
- AI Monitoring – EU AI Act Article 89 on monitoring and measurement aligns with NIST AI RMF Measure 4.2 and Govern 2.1, and ISO 42001 Clause 9.1.
- AI Governance – EU AI Act Article 10 on data governance corresponds to NIST AI RMF Govern 1.1 and Manage 1.1, and ISO 42001 Clauses 9.2–9.3.
Understanding these overlaps is critical for global compliance. Unlike NIST AI RMF and ISO 42001, the EU AI Act is legally binding for organizations operating in Europe. Starting with the NIST AI RMF can help organizations streamline ISO/IEC 42001:2023 implementation and ensure alignment with legally mandated frameworks like the AI Act.
How to Certify Trustworthy AI Operations
Implementing the NIST AI Risk Management Framework (AI RMF) and ISO/IEC 42001:2023 is only part of the journey toward responsible AI. To demonstrate compliance and provide assurance to stakeholders, organizations must undergo a formal assessment process.
The NIST AI RMF is unique in that it is a voluntary framework with no NIST-recognized certification. Organizations are encouraged to implement its guidelines, but formal audits or certifications by NIST do not yet exist. However, third-party organizations can provide assurance through rigorous assessments using transparent metrics and findings. Partnering with experts experienced in NIST and other regulatory frameworks ensures reliable and actionable results. A well-executed NIST AI RMF implementation also facilitates other AI certifications down the line.
In contrast, ISO/IEC 42001:2023 is a certifiable standard. Third-party assessors follow templates prescribed by ISO/IEC to conduct formal audits that result in ISO 42001 certification. In many cases, assessors can verify compliance across multiple frameworks, such as NIST AI RMF, ISO 42001, and the EU AI Act, in a single, integrated assessment Engaging experienced, qualified assessors maximizes compliance ROI and provides confidence to regulators, partners and stakeholders.
Working with a compliance and security advisor who is well-versed in NIST, ISO and other regulatory contexts is the most effective way to determine how your organization should implement and certify trustworthy AI operations.
Optimize Your AI Compliance Today
<p>Preparing for AI compliance and ensuring smooth AI operations in 2025 and beyond requires robust infrastructure development and strategic architecture deployment. While NIST AI RMF and ISO/IEC 42001:2023 are not the only frameworks available, they provide an excellent starting point, especially since implementing the NIST AI RMF can streamline ISO 42001 adoption and assessment.
At RSI Security, we help organizations optimize AI governance and broader IT environments through flexible, expert-led support. Our team collaborates with your organization to design and deploy controls, prepare for assessments, and provide assurance to stakeholders. By establishing disciplined processes upfront, organizations gain greater operational flexibility and compliance confidence over the long term.
<p>To learn more about how RSI Security can support your NIST AI RMF and ISO/IEC 42001 initiatives, contact RSI Security today and start building a trustworthy, compliant AI program.
