Artificial Intelligence Policy Tracker
Voluntary guidance Impact assessment United States Voluntary standard

Map context, intended use and potential impacts (Map)

Download: JSON · MarkdownUnder NIST AI RMF, MAP function

Source-linked · linked to the official source, not yet confirmed by a reviewer (a factual check against the official source, not a legal review or legal advice)
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Source-linked
— linked to the official source, not yet confirmed by a reviewer.
Verification policy and current standing · a factual check, not legal advice.
No change recorded as of 26 Sep 2026 · official source last checked
On this page 9 sections

In brief

Map context, intended use and potential impacts (Map) is a voluntary measure under the NIST AI RMF in the United States (MAP function). Map establishes the context: intended purposes, users, deployment settings, legal requirements, risk categorisation, benefits and costs, and impacts on individuals, groups, communities and society. The record carries 1 evidence example and mappings to 1 framework.

Instrument
NIST AI RMF
Jurisdiction
United States
Nature
Voluntary guidance
Source reference
MAP function
Who it binds
Provider / developer, Deployer / user organisation
Evidence examples
1
Framework mappings
ISO/IEC 42001:2023
Controls that meet it
3
Official source
Open official text
Verification
Source-linked

What does it require?

Map establishes the context: intended purposes, users, deployment settings, legal requirements, risk categorisation, benefits and costs, and impacts on individuals, groups, communities and society.

Practical action

Produce a system card or context document before development starts.

Who does it apply to?

Voluntary; any organisation adopting the framework.

Which controls meet this duty?

Satisfies: the control, operated properly, does the work the duty asks for. Supports: it contributes but the duty needs more. Each control page lists every other duty it serves, so work done once can be counted once.

  • satisfiesProcessAI system owner · once per ai system
    AI impact and fundamental-rights impact assessment

    Serves 11 recorded duties · evidence: AI impact assessment, Impact assessment approval, Impact assessment procedure and template

    Context, affected people and impact analysis produced before development.

  • supportsProcessAI system owner · once per ai system
    AI risk assessment and lifecycle risk register

    Serves 12 recorded duties · evidence: AI system risk assessment, Per-system AI risk register, Residual-risk acceptance

    Risk categorisation and benefit-cost analysis.

  • supportsProcessAI governance lead · continuous
    AI system inventory and classification

    Serves 11 recorded duties · evidence: AI system register, Risk-tier classification sign-off, AI intake and classification procedure

    Intended purpose, users and settings recorded at intake.

Templates that cover this duty

Generated from the records. Free · no account · links emailed to your work address. This duty is cited in each file with its source reference and a link back here.

All 7 templates that cover it →

What evidence would a reviewer expect?

Evidence examples
EvidenceTypeNotes
AI system context and impact documentdocument

Framework mappings

Original editorial crosswalks. They cite clause numbers only and reproduce no standard text; confidence reflects how direct the mapping is.

See every United States duty mapped this way →

Framework mappings table
FrameworkReferenceNoteConfidence
ISO/IEC 42001:2023Clause 6.1.4 AI system impact assessmentOriginal editorial mapping.high

Frequently asked questions

Is this a legal requirement?

No. It is voluntary guidance under NIST AI RMF; following it is expected or recommended rather than required by law.

Who must comply with this obligation?

Voluntary; any organisation adopting the framework.

What evidence shows compliance?

A reviewer would expect: AI system context and impact document.

Which frameworks map to this obligation?

It is mapped to ISO/IEC 42001:2023 Clause 6.1.4 AI system impact assessment. These are editorial crosswalks with a stated confidence, not official mappings.

Which controls satisfy this obligation?

AI risk assessment and lifecycle risk register; AI system inventory and classification; AI impact and fundamental-rights impact assessment.

What should an organisation do in practice?

Produce a system card or context document before development starts.

Cite this record

AIPolicyTracker (2026). “Map context, intended use and potential impacts (Map) (NIST AI RMF)” [AIPT-OBL-0113, verified 26 September 2026 by Bhaskar Bhatt]. https://aipolicytracker.org/id/AIPT-OBL-0113 (accessed 27 October 2026). Data licensed CC BY 4.0.

Permanent id AIPT-OBL-0113: it never changes or gets reused, and its address keeps working if this page moves.

Cite the official text alongside it: Artificial Intelligence Risk Management Framework (AI RMF 1.0), National Institute of Standards and Technology, https://nvlpubs.nist.gov/nistpubs/ai/NIST.AI.100-1.pdf.

BibTeX
@misc{aipolicytracker2026_mapcontextintendeduseand,
  author       = {{AIPolicyTracker}},
  title        = {{Map context, intended use and potential impacts (Map) (NIST AI RMF)}},
  year         = {2026},
  howpublished = {\url{https://aipolicytracker.org/obligations/us-nist-ai-rmf-map}},
  url          = {https://aipolicytracker.org/obligations/us-nist-ai-rmf-map},
  urldate      = {2026-10-27},
  note         = {Data licensed CC BY 4.0. Accessed 27 October 2026}
}

Change history

No change to this record's tracked fields has been recorded since 15 October 2026, when field-level history began.

Similar obligations in other instruments

Disclaimer: informational only, not legal advice. Verify every claim against the linked official sources and consult a qualified lawyer before acting.