NIST AI RMF Map Function

NIST AI RMF 1.0 (NIST AI 100-1, January 2023) is voluntary guidance from the National Institute of Standards and Technology (NIST). MAP is one of the four functions of its Core. Section 5.2 of NIST AI 100-1 starts as follows: "The MAP function establishes the context to frame risks related to an AI system." Table 2 divides MAP into five categories (MAP 1 to MAP 5) and 18 subcategories. Each subcategory gives an outcome.

NIST gives this information on its AI RMF page: "The AI RMF 1.0 is being revised as part of the White House AI Action Plan." As of October 2026, no new version is available. The MAP outcomes on this page come from NIST AI 100-1 of January 2023 (see NIST AI RMF).

Primary sources

NIST AI 100-1, Artificial Intelligence Risk Management Framework (AI RMF 1.0), January 2023: Section 5.2 (Map) and Table 2 (categories and subcategories for the MAP function). NIST AI 100-1 (PDF).

How Map fits into NIST AI RMF 1.0

In the Executive Summary, NIST AI 100-1 writes that GOVERN "applies to all stages of organizations’ AI risk management processes and procedures", and that MAP, MEASURE, and MANAGE "can be applied in AI system-specific contexts and at specific stages of the AI lifecycle" (see NIST AI RMF).

NIST AI 100-1 gives these points about the MAP function in Section 5.2:

• The AI lifecycle has many related tasks and many AI actors. These relations "can make it difficult to reliably anticipate impacts of AI systems."
• The information from the MAP function helps to prevent negative risk. It also "informs decisions for processes such as model management, as well as an initial decision about appropriateness or the need for an AI solution."
• "Outcomes in the MAP function are the basis for the MEASURE and MANAGE functions." Without information about the context and about the risks in that context, "risk management is difficult to perform."
• The work on MAP "is enhanced by incorporating perspectives from a diverse internal team and engagement with those external to the team that developed or deployed the AI system." NIST adds: "Engagement with external collaborators, end users, potentially impacted communities, and others may vary based on the risk level of a particular AI system, the makeup of the internal team, and organizational policies."
• "After completing the MAP function, Framework users should have sufficient contextual knowledge about AI system impacts to inform an initial go/no-go decision about whether to design, develop, or deploy an AI system."
• If the decision is to continue, NIST recommends that organizations use MEASURE and MANAGE, together with the policies and procedures of GOVERN.
• "It is incumbent on Framework users to continue applying the MAP function to AI systems as context, capabilities, risks, benefits, and potential impacts evolve over time."

In Section 5, NIST AI 100-1 writes that, after the GOVERN outcomes, "most users of the AI RMF would start with the MAP function". For the conditions on the sequence of the functions, see The four functions of the Core.

The five MAP categories

NIST AI 100-1 Table 2 divides the MAP function into five categories and 18 subcategories:

MAPContext to frame AI risks, NIST AI RMF 1.0

MAP 1Context is established and understood (6 subcategories)

MAP 2Categorization of the AI system (3 subcategories)

MAP 3Capabilities, targeted usage, goals, benefits, and costs, compared with appropriate benchmarks (5 subcategories)

MAP 4Risks and benefits of all components, including third-party software and data (2 subcategories)

MAP 5Impacts to individuals, groups, communities, organizations, and society (2 subcategories)

MAP 1

NIST AI 100-1, Table 2, MAP 1: Context is established and understood.

MAP 1.1

NIST AI 100-1, Table 2, MAP 1.1: Intended purposes, potentially beneficial uses, context-specific laws, norms and expectations, and prospective settings in which the AI system will be deployed are understood and documented. Considerations include: the specific set or types of users along with their expectations; potential positive and negative impacts of system uses to individuals, communities, organizations, society, and the planet; assumptions and related limitations about AI system purposes, uses, and risks across the development or product AI lifecycle; and related TEVV and system metrics.

MAP 1.1 does not identify the laws that apply. NIST AI 100-1 Appendix D includes this item: "Be law- and regulation-agnostic. The Framework should support organizations’ abilities to operate under applicable domestic and international legal or regulatory regimes."

MAP 1.2

NIST AI 100-1, Table 2, MAP 1.2: Interdisciplinary AI actors, competencies, skills, and capacities for establishing context reflect demographic diversity and broad domain and user experience expertise, and their participation is documented. Opportunities for interdisciplinary collaboration are prioritized.

MAP 1.3

NIST AI 100-1, Table 2, MAP 1.3: The organization’s mission and relevant goals for AI technology are understood and documented.

MAP 1.4

NIST AI 100-1, Table 2, MAP 1.4: The business value or context of business use has been clearly defined or – in the case of assessing existing AI systems – re-evaluated.

MAP 1.5

NIST AI 100-1, Table 2, MAP 1.5: Organizational risk tolerances are determined and documented.

The AI RMF does not set a risk tolerance for organizations (NIST AI 100-1, Section 1.2.2). GOVERN 1.3 is about the necessary level of risk management work, which follows from the risk tolerance of the organization (see NIST AI RMF).

MAP 1.6

NIST AI 100-1, Table 2, MAP 1.6: System requirements (e.g., “the system shall respect the privacy of its users”) are elicited from and understood by relevant AI actors. Design decisions take socio-technical implications into account to address AI risks.

MAP 2

NIST AI 100-1, Table 2, MAP 2: Categorization of the AI system is performed.

MAP 2.1

NIST AI 100-1, Table 2, MAP 2.1: The specific tasks and methods used to implement the tasks that the AI system will support are defined (e.g., classifiers, generative models, recommenders).

MAP 2.2

NIST AI 100-1, Table 2, MAP 2.2: Information about the AI system’s knowledge limits and how system output may be utilized and overseen by humans is documented. Documentation provides sufficient information to assist relevant AI actors when making decisions and taking subsequent actions.

MAP 2.3

NIST AI 100-1, Table 2, MAP 2.3: Scientific integrity and TEVV considerations are identified and documented, including those related to experimental design, data collection and selection (e.g., availability, representativeness, suitability), system trustworthiness, and construct validation.

MAP 3

NIST AI 100-1, Table 2, MAP 3: AI capabilities, targeted usage, goals, and expected benefits and costs compared with appropriate benchmarks are understood.

MAP 3.1

NIST AI 100-1, Table 2, MAP 3.1: Potential benefits of intended AI system functionality and performance are examined and documented.

MAP 3.2

NIST AI 100-1, Table 2, MAP 3.2: Potential costs, including non-monetary costs, which result from expected or realized AI errors or system functionality and trustworthiness – as connected to organizational risk tolerance – are examined and documented.

MAP 1.5 is the subcategory for the risk tolerances of the organization.

MAP 3.3

NIST AI 100-1, Table 2, MAP 3.3: Targeted application scope is specified and documented based on the system’s capability, established context, and AI system categorization.

MAP 3.4

NIST AI 100-1, Table 2, MAP 3.4: Processes for operator and practitioner proficiency with AI system performance and trustworthiness – and relevant technical standards and certifications – are defined, assessed, and documented.

MAP 3.5

NIST AI 100-1, Table 2, MAP 3.5: Processes for human oversight are defined, assessed, and documented in accordance with organizational policies from the GOVERN function.

MAP 4

NIST AI 100-1, Table 2, MAP 4: Risks and benefits are mapped for all components of the AI system including third-party software and data.

MAP 4.1

NIST AI 100-1, Table 2, MAP 4.1: Approaches for mapping AI technology and legal risks of its components – including the use of third-party data or software – are in place, followed, and documented, as are risks of infringement of a third party’s intellectual property or other rights.

MAP 4.2

NIST AI 100-1, Table 2, MAP 4.2: Internal risk controls for components of the AI system, including third-party AI technologies, are identified and documented.

MAP 5

NIST AI 100-1, Table 2, MAP 5: Impacts to individuals, groups, communities, organizations, and society are characterized.

MAP 5.1

NIST AI 100-1, Table 2, MAP 5.1: Likelihood and magnitude of each identified impact (both potentially beneficial and harmful) based on expected use, past uses of AI systems in similar contexts, public incident reports, feedback from those external to the team that developed or deployed the AI system, or other data are identified and documented.

The sources of data in MAP 5.1 are alternatives: you can use one or more of them. You can also use other data, because the last item is "or other data". In Section 1.1 of NIST AI 100-1, risk is "the composite measure of an event’s probability of occurring and the magnitude or degree of the consequences of the corresponding event."

MAP 5.2

NIST AI 100-1, Table 2, MAP 5.2: Practices and personnel for supporting regular engagement with relevant AI actors and integrating feedback about positive, negative, and unanticipated impacts are in place and documented.

MAP in Modulos

In Modulos, NIST AI RMF 1.0 is available as two Frameworks with the name NIST AI RMF. You add MFF-3 to an AI System and OFF-3 to the organization AI System. The two Frameworks have Requirements for the MAP function, and each Requirement has the name of one subcategory. The Requirement for Map 5.1 is only in OFF-3. Each other MAP subcategory has a Requirement in MFF-3, and some also have one in OFF-3. For the Requirement of each MAP subcategory and the steps that Modulos recommends, see Operationalizing NIST AI RMF in Modulos.

Where to go next

The AI RMF to ISO/IEC 42001 crosswalk that NIST shows on its AI Resource Center has a row for each MAP subcategory. For this crosswalk, and to compare the AI RMF with the EU AI Act, see NIST AI RMF.

NIST AI RMF overview

The AI RMF, its four functions, its profiles, and its relation to ISO/IEC 42001 and the EU AI Act

NIST AI RMF Govern function

The GOVERN categories and subcategories of Table 1

NIST AI RMF Measure function

The MEASURE categories and subcategories of Table 3

NIST AI RMF Manage function

The MANAGE categories and subcategories of Table 4

Sources of this page

• NIST AI 100-1 — Artificial Intelligence Risk Management Framework (AI RMF 1.0), January 2023: Executive Summary, Sections 1.1, 1.2.2, 5, 5.1, and 5.2, Table 1 (GOVERN 1.3), Table 2, and Appendix D. NIST AI 100-1 (PDF).
• NIST AI RMF page — the NIST page about the AI RMF. As of October 2026, it gives this text: "The AI RMF 1.0 is being revised as part of the White House AI Action Plan." AI Risk Management Framework.
• NIST AI RMF Playbook — a voluntary companion resource from NIST, with suggested actions for the outcomes of the Core. Section 5.2 of NIST AI 100-1 refers to it for practices to map AI risks. AI RMF Playbook.
• AI RMF to ISO/IEC 42001 crosswalk — on the crosswalks page of the NIST AI Resource Center. It has a row for each MAP subcategory. AI RMF crosswalks.

Disclaimer

This page gives general information about the MAP function. It is not legal advice.