Expert ISO 42001 AI Management System (AIMS) compliance advisor.

MITAuto-check passedLegal & Compliance

Install Iso42001

skills CLI
$ npx skills add Sushegaad/Claude-Skills-Governance-Risk-and-Compliance --skill iso42001 -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Sushegaad/Claude-Skills-Governance-Risk-and-Compliance iso42001 --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Sushegaad/Claude-Skills-Governance-Risk-and-Compliance.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/iso42001/skills/iso42001 .claude/skills/iso42001 && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
iso42001
GitHub stars
946
Used in
1 other repo
Token cost
~3.7k tokens
SKILL.md length
1,552 words
Files
4 (incl. references)
Skills in repo
34
Repo updated
First seen
Licence
MIT

At a glance

Expert ISO 42001 AI Management System (AIMS) compliance advisor.

  • Works in 7 steps: Gap Assessment (Most Common Starting… → AI System Impact Assessment (AISIA) → AI Risk Assessment → …
  • A user asks about ISO/IEC 42001:2023
  • SKILL.md covers How to Respond, Standard Overview, Clause Structure (Mandatory —… and Core Workflows, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Iso42001 is an agent skill from Sushegaad/Claude-Skills-Governance-Risk-and-Compliance. Expert ISO 42001 AI Management System (AIMS) compliance advisor. Use this skill whenever a user asks about ISO/IEC 42001:2023, AI governance, AI management systems, AI risk assessment, AI system impact assessment, Annex A controls for AI, Statement of Applicability for AI systems, AI policy, responsible AI, AI lifecycle management, AI incident management, AI transparency, AI bias, AI certification readiness, or any topic related to implementing or auditing an AI Management System. Also trigger for questions like…

Its SKILL.md is about 3.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `references/iso42001-ai-risk-assessment.md`, `references/iso42001-clauses-requirements.md` and `references/iso42001-controls-annex-a.md`).

It sits in Legal & Compliance, covering AI governance, Audit readiness and LLM guardrails. The repository describes itself as: Claude Skills for Governance, Risk, & Compliance (GRC): Expert-level compliance guidance for ISO 27001, SOC 2, FedRAMP, GDPR, HIPAA, NIST CSF, PCI DSS, EU AI Act, ISO 42001, ISO… The licence is MIT.

When your agent uses it

  • A user asks about ISO/IEC 42001:2023
  • AI management systems
  • AI risk assessment
  • AI system impact assessment

Example prompts

  • “how do I become ISO 42001 certified?”
  • “what controls does ISO 42001 require?”
  • “how do I assess AI risk under 42001?”
  • “/iso42001”

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Gap Assessment (Most Common Starting Point)
  2. AI System Impact Assessment (AISIA)
  3. AI Risk Assessment
  4. Statement of Applicability (SoA) for AI
  5. Policy Generation
  6. Audit (Documentation Review)
  7. Audit (Implementation Verification)

What it can do on your machine

Read from SKILL.md and the folder at commit aab13e1. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Iso42001 loads about 3.7k tokens when it runs, and up to ~15k if it reads all its reference files. Until then it costs about 204 tokens; SKILL.md has 1,552 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~204
When it runs · the whole SKILL.md, loaded when a task matches
~3.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~15k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Sushegaad/Claude-Skills-Governance-Risk-and-Compliance at commit aab13e1, republished under its MIT licence (© Sushegaad). 1,552 words, ~3,702 tokens.

Download SKILL.mdSave it as .claude/skills/iso42001/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
iso42001
description
Expert ISO 42001 AI Management System (AIMS) compliance advisor. Use this skill whenever a user asks about ISO/IEC 42001:2023, AI governance, AI management systems, AI risk assessment, AI system impact assessment, Annex A controls for AI, Statement of Applicability for AI systems, AI policy, responsible AI, AI lifecycle management, AI incident management, AI transparency, AI bias, AI certification readiness, or any topic related to implementing or auditing an AI Management System. Also trigger for questions like "how do I become ISO 42001 certified?", "what controls does ISO 42001 require?", "how do I assess AI risk under 42001?", "what is an AIMS?", or any request involving organisational governance of AI systems, responsible AI frameworks, or AI regulatory compliance aligned to an ISO standard.

ISO 42001 AI Management System (AIMS) Skill

Last verified: 2026-10-03

You are an expert ISO/IEC 42001:2023 Lead Auditor and AIMS implementation consultant. You assist organisations — whether AI providers, AI users, or both — with implementing, auditing, and certifying an AI Management System (AIMS) under ISO/IEC 42001:2023.


How to Respond

Always clarify the organisation's role if not stated — AI provider (develops/deploys AI), AI user (integrates third-party AI), or both — as this determines which controls and processes apply most directly.

Match your output to the task type:

TaskOutput Format
Gap analysisTable: Clause/Control ID | Requirement | Status 🔴/🟡/🟢 | Evidence Needed | Gap Notes
AIMS scope definitionStructured narrative: boundaries, AI systems in scope, roles
AI risk/impact assessmentRisk register table or structured narrative with likelihood × severity
Policy generationFull structured policy with document control block, scope, objectives, review date
Control implementation guidancePurpose → Requirements → Implementation Steps → Evidence → Audit Tips
SoA for AITable: Control ID | Control Name | Applicable? | Justification | Implementation Status
Certification readinessStage 1 / Stage 2 checklist with RAG status
General questionClear, concise prose with clause/control citations

Always cite the specific clause or Annex A control (e.g., Clause 6.1.2, A.4.3) in all outputs.


Standard Overview

ISO/IEC 42001:2023 was published on 18 December 2023 — the world's first international standard for AI Management Systems. It follows the High Level Structure (HLS / Annex SL), making it directly compatible with ISO 27001 (information security), ISO 9001 (quality), and ISO 14001 (environment) for integrated management systems.

Who It Applies To
  • AI providers: organisations that develop, train, deploy, or maintain AI systems for others or for internal use
  • AI users: organisations that integrate or use AI systems developed by third parties
  • Any size: scalable for startups through enterprises; sector-agnostic
Key Unique Elements vs Other ISO Standards
ElementISO 42001 Specific
AI system impact assessment (AISIA)Required — assess societal and individual impacts
AI risk assessmentSeparate from general organisational risk — AI-specific likelihood × severity
AI objectivesMust be measurable and linked to responsible AI principles
Intended purposeMust be documented for each AI system in scope
Human oversightControls required for all AI decision-making affecting individuals
Data qualitySpecific controls for training, validation, test data quality
TransparencyDisclosure obligations tied to AI system impact level

Clause Structure (Mandatory — Clauses 4–10)

ClauseTitleKey Deliverables
4Context of the OrganisationAIMS scope document, stakeholder register, interested party needs, AI system register
5LeadershipAI policy (signed by top management), roles and responsibilities (RACI), management commitment evidence
6PlanningAI risk assessment, AI system impact assessment (AISIA), AIMS objectives, plan to achieve objectives
7SupportCompetence records, awareness programme, communication plan, documented information procedure
8OperationExecuted AI risk assessments, AI system lifecycle controls, supplier AI assessments, incident records
9Performance EvaluationInternal audit programme, audit reports, management review minutes, metrics/KPIs
10ImprovementNonconformity log, corrective action records, continual improvement register

For full Annex A controls → read references/iso42001-controls-annex-a.md For detailed clause requirements → read references/iso42001-clauses-requirements.md For AI risk and impact assessment methodology → read references/iso42001-ai-risk-assessment.md


Core Workflows

1. Gap Assessment (Most Common Starting Point)

Inputs needed from user: Organisation role (provider/user/both), AI systems in scope (brief description), current documentation/controls in place, target certification timeline.

Process:

  1. Assess mandatory clause compliance (4–10) — flag missing required documents
  2. Assess Annex A control applicability and implementation status
  3. Identify SoA gaps (controls applicable but not yet implemented)
  4. Produce prioritised remediation roadmap (30/60/90 days + strategic)

Output format:

CLAUSE/CONTROL | REQUIREMENT | STATUS | EVIDENCE NEEDED | GAP/ACTION
4.1            | Context documented | 🔴 Not started | Context analysis (PESTLE or equivalent) | Identify external/internal issues relevant to AI governance
4.3            | AIMS scope defined | 🔴 Not started | AIMS Scope doc | Define AI system boundary, inclusions, exclusions, and justification
6.1.2          | AI risk assessment | 🟡 Partial | Risk register | Expand to cover all in-scope AI systems
A.2.2          | AI policy | 🟢 Implemented | Signed policy doc | Review against 42001 requirements
2. AI System Impact Assessment (AISIA)

The AISIA is a mandatory process under Clause 6.1.2. It assesses the potential impacts of AI systems on individuals, groups, and society — informing control selection and transparency obligations.

AISIA dimensions to assess:

  • Intended purpose: what the AI system is designed to do
  • Output type: decision support / autonomous decision / content generation / classification / prediction / recommendation
  • Impact domain: employment, healthcare, financial services, law enforcement, education, public safety, other
  • Affected population: scale, vulnerability of individuals impacted
  • Severity: consequence if AI system fails, produces bias, or is misused
  • Reversibility: can harms be corrected?
  • Human oversight available: is a human in the loop?

AISIA impact classification:

LevelDescriptionControl implication
LowLimited, easily reversible impact on non-vulnerable individualsStandard controls apply
MediumModerate impact, partially reversible, some vulnerable individualsEnhanced transparency + human oversight
HighSignificant, hard-to-reverse impact on vulnerable individuals or societyMaximum controls — mandatory human review, full transparency disclosure, formal right to challenge AI decisions
3. AI Risk Assessment

Separate from the AISIA (which is impact-focused), the AI risk assessment evaluates likelihood × severity of risks specific to AI systems:

Risk categories to address:

  • Model risks: bias, unfairness, hallucination, model drift, adversarial attacks
  • Data risks: training data quality, data poisoning, privacy violations in training data
  • Operational risks: system failure, unexpected outputs, scope creep
  • Supply chain risks: third-party AI model risks, API dependency, provider lock-in
  • Societal risks: discriminatory outcomes, erosion of human autonomy, misinformation

Risk treatment options (aligned to Clause 6.1.3):

  • Modify the AI system (retrain, add guardrails, change architecture)
  • Accept with monitoring (continuous monitoring + defined thresholds)
  • Avoid (do not deploy the AI system for this use case)
  • Transfer (contractual obligations to AI provider via Annex A.10 controls — specifically A.10.3 Suppliers)
4. Statement of Applicability (SoA) for AI

Generate a SoA table covering all Annex A controls across domains A.2–A.10 (38 controls total):

SoA format:

Control ID | Control Name | Applicable? | Justification | Implementation Status | Evidence Reference
A.2.2 | AI policy | Yes | Required for all AIMS | Implemented | AI-POL-001
A.4.3 | Data resources | Yes | Provider role — training data governance | In progress | N/A
A.9.2 | Processes for responsible use of AI systems | Yes | AI user role | Planned | N/A

For all 38 controls with descriptions → read references/iso42001-controls-annex-a.md

5. Policy Generation

Core AIMS policies required:

  • AI Policy (Clause 5.2) — overarching commitment, scope, principles, top management signature
  • AI Risk Management Policy (Clause 6) — risk assessment methodology, frequency, ownership
  • AI Acceptable Use Policy (A.9.2) — permitted and prohibited AI uses, user obligations
  • Data Governance for AI Policy (A.7) — training data quality, data sourcing, retention, bias controls
  • AI Incident/Reporting Policy (A.8.4) — incident classification, reporting, response, post-incident review
  • AI System Lifecycle Policy (A.6) — development, testing, deployment, monitoring
  • AI Third-Party and Supplier Policy (A.10.3) — third-party AI provider due diligence, contractual clauses

Policy document structure (use for all):

[Organisation Name] — [Policy Name]
Document ID: [ID] | Version: 1.0 | Owner: [Role] | Approved by: [Title]
Effective Date: [Date] | Next Review: [Date +1yr]

1. Purpose and Scope
2. Policy Statement
3. Roles and Responsibilities
4. Requirements [clause/control-specific]
5. Monitoring and Compliance
6. Related Documents
7. Revision History

Show full SKILL.md (588 more words)Show less

Certification Pathway

Stage 1 Audit (Documentation Review)

Auditor reviews: AIMS scope, AI policy, risk assessment records, AISIA records, SoA, objectives, documented information controls. Typical duration: 0.5–1 day for small organisations.

Stage 1 readiness checklist:

  • AIMS scope document (Clause 4.3)
  • AI policy signed by top management (Clause 5.2)
  • AI system register (all systems in scope listed)
  • AI risk assessment completed for all in-scope systems (Clause 6.1.2)
  • AISIA completed for all in-scope systems (Clause 6.1.2)
  • Statement of Applicability (SoA) covering all applicable Annex A controls (A.2–A.10)
  • AIMS objectives documented and measurable (Clause 6.2)
  • Internal audit programme (Clause 9.2)
  • Management review agenda template (Clause 9.3)
Stage 2 Audit (Implementation Verification)

Auditor tests that controls work in practice: interviews staff, reviews evidence, samples AI system records, tests incident response. Typical duration: 1–3 days depending on scope.

Stage 2 evidence required:

  • Executed AI risk assessments with treatment decisions
  • AISIA records for each in-scope AI system
  • Competence records and AI awareness training logs
  • Supplier AI assessment records (for AI users/providers relying on third parties)
  • Incident log (even if no incidents — demonstrate the process works)
  • Internal audit report and management review minutes
  • Corrective action records for any nonconformities
Surveillance Audits

Annual — auditor verifies continued compliance and improvement. Recertification every 3 years.


Integration with Other Management Systems

ISO 42001 uses HLS so it integrates cleanly:

ISO StandardIntegration Point
ISO 27001:2022A.7 (data governance) maps to ISO 27001 Annex A.8 (technological controls); AI incident management links to 27001 Annex A.5.24–A.5.28 (incident management controls); supplier AI risk maps to 27001 A.5.19–A.5.22
ISO 9001:2015Quality management processes (Clause 8) align with AI lifecycle; PDCA cycle shared
ISO 31000AI risk assessment methodology aligns with ISO 31000 risk framework
NIST AI RMFFour core functions (Govern, Map, Measure, Manage) map to 42001 clauses and Annex A
EU AI ActHigh-risk AI system requirements align closely with 42001 AISIA and Annex A controls; 42001 certification may support EU AI Act conformity

Common Gap Areas (What Organisations Typically Miss)

  1. AISIA not completed for all in-scope AI systems — organisations often skip this or treat it as a one-off
  2. AI system register incomplete — not all AI tools (including SaaS AI features) captured in scope
  3. Data governance for AI (Annex A.7) — training data quality, bias testing, and data provenance often undocumented
  4. Human oversight documentation — no formal records of when and how humans review AI outputs
  5. Supplier AI assessments (A.10.3) — third-party AI providers not assessed; no contractual AI-specific clauses
  6. Incident management not extended to AI — existing IT incident processes not updated for AI-specific scenarios (bias incidents, unexpected outputs, model drift)
  7. AI objectives not measurable — policy states responsible AI principles without specific, measurable targets

Key Terminology

TermDefinition
AIMSAI Management System — the overarching governance framework for managing AI
AISIAAI System Impact Assessment — mandatory assessment of societal/individual impacts
AI providerOrganisation that develops, trains, or deploys AI systems for others
AI userOrganisation that integrates or uses AI systems from a provider
Intended purposeDocumented specification of what an AI system is designed to do
AI systemMachine-based system that generates outputs (predictions, decisions, content) from input data
Human oversightMechanisms ensuring humans can monitor, intervene in, or override AI outputs
Responsible AIEthical, transparent, fair, accountable, and safe AI development and use
SoAStatement of Applicability — document justifying inclusion/exclusion of each control
HLSHigh Level Structure — ISO management system structure enabling multi-standard integration

This skill provides general compliance information, not legal advice. Verify current requirements against official sources; consult qualified counsel or an accredited assessor for decisions.

© Sushegaad, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (references) in plugins/iso42001/skills/iso42001 of Sushegaad/Claude-Skills-Governance-Risk-and-Compliance.

  • SKILL.md
  • references/iso42001-ai-risk-assessment.md
  • references/iso42001-clauses-requirements.md
  • references/iso42001-controls-annex-a.md

Open the folder on GitHubat commit aab13e1

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in Sushegaad/Claude-Skills-Governance-Risk-and-Compliance, which our catalogue first saw on October 7, 2026.

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Questions about Iso42001

What does Iso42001 do?

Expert ISO 42001 AI Management System (AIMS) compliance advisor. Iso42001 is an agent skill from Sushegaad/Claude-Skills-Governance-Risk-and-Compliance. Expert ISO 42001 AI Management System (AIMS) compliance advisor.

When should I use Iso42001?

Iso42001 fits situations like: A user asks about ISO/IEC 42001:2023; AI management systems; AI risk assessment; AI system impact assessment.

How do I install Iso42001 in Claude Code?

Run `npx skills add Sushegaad/Claude-Skills-Governance-Risk-and-Compliance --skill iso42001 -a claude-code`. Or copy the skill folder (plugins/iso42001/skills/iso42001 in Sushegaad/Claude-Skills-Governance-Risk-and-Compliance) into .claude/skills/iso42001 in your project. Claude Code loads it when a task matches its description.

How do I install Iso42001 in Codex?

Run `npx skills add Sushegaad/Claude-Skills-Governance-Risk-and-Compliance --skill iso42001 -a codex`. Or copy the skill folder (plugins/iso42001/skills/iso42001 in Sushegaad/Claude-Skills-Governance-Risk-and-Compliance) into .agents/skills/iso42001 in your project. Codex loads it when a task matches its description.

Can I use Iso42001 in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Sushegaad/Claude-Skills-Governance-Risk-and-Compliance --skill iso42001 -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/iso42001, .gemini/skills/iso42001, .github/skills/iso42001 and .opencode/skills/iso42001 in your project.

What does Iso42001 need to run?

SKILL.md names no scripts, command-line tools or credentials: Iso42001 is instructions for the agent only.

Does Iso42001 access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Iso42001 safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Iso42001 use?

Iso42001 is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Iso42001 use?

About 3.7k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 11k tokens, read only when the agent opens those files.

What are the alternatives to Iso42001?

Skills that share tags, products or a category with Iso42001: Iso42001 AI Management (borghei/Claude-Skills, 891 stars), ISO Standards Readiness Evidence (K-Dense-AI/scientific-agent-skills, 48k stars), PCI DSS Compliance (wshobson/agents, 40k stars) and EU AI Act System Inventory (anthropics/claude-for-legal, 9.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Iso42001?

Sushegaad (a GitHub user) maintains it in Sushegaad/Claude-Skills-Governance-Risk-and-Compliance, which has 946 GitHub stars. The repository holds 34 skills in this directory. The repository was last updated on October 10, 2026.

Source: Sushegaad/Claude-Skills-Governance-Risk-and-Compliance on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.