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ISO 42001 Facility Management System
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ISO 42001 Facility Management System

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ISO 42001 Facility Management System is the world’s first international standard for an Artificial Intelligence Management System (AIMS).

Its short description is: ISO 42001 specifies requirements for establishing, implementing, maintaining, and continually improving an AIMS within any organization that provides or uses AI systems. It provides a systematic framework to ensure the responsible, ethical, and transparent development and use of AI, helping organizations manage associated risks (like bias and data privacy) while fostering trust and aligning with regulatory requirements like the EU AI Act.

Note: The standard for a Facility Management System is actually ISO 41001, not ISO 42001. ISO 41001 provides a framework to deliver efficient and effective facility management services.

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ISO 42001 Facility Management System

The purpose of ISO/IEC 42001:2023 is to provide a framework for establishing, implementing, maintaining, and continually improving an AIMS within an organization. It focuses on the responsible development, provision, and use of Artificial Intelligence systems, addressing concerns like:

  • Ethics and Transparency
  • AI Risk Management (including bias and accountability)
  • Data Quality and Governance
  • Security and Safety

The standard for Facility Management is ISO 41001.

ISO 41001:2018 (Facility management — Management systems — Requirements with guidance for use) is the actual standard that specifies the requirements for a Facility Management System.

What are the main clauses of ISO/IEC 42001:2023

ISO/IEC 42001:2023, the standard for an Artificial Intelligence Management System (AIMS), follows the common High-Level Structure (HLS) of all modern ISO management system standards (like ISO 27001 or ISO 9001).

The core, auditable requirements of the standard are contained in Clauses 4 through 10, which follow the Plan-Do-Check-Act (PDCA) cycle for continual improvement:

Plan (Clauses 4, 5, 6)

 

Clause Focus Key Requirements
4 Context of the Organization Determine the external and internal issues, the needs of interested parties (e.g., users, regulators), and define the scope of the AIMS.
5 Leadership Top management must demonstrate commitment by establishing the AI Policy, defining AI objectives, and assigning clear roles and responsibilities.
6 Planning Determine the risks and opportunities for AI systems. Crucially, this requires:
– AI Risk Assessment
– AI System Impact Assessment (AIIA) (focusing on impact on individuals and society)
– Planning to address these risks and opportunities.
7 Support Ensure the necessary resources are in place, including competent personnel, awareness programs, communication processes, and documented information (policies, procedures, records).

Do (Clause 8)

 

Clause Focus Key Requirements
8 Operation The implementation of the AIMS, including:
– Operational planning and control.
– Managing the AI system lifecycle (development, deployment, etc.).
– Implementing the risk treatment plan and controls selected from Annex A.
– Managing data for AI systems (quality, acquisition).

Check and Act (Clauses 9, 10)

 

Clause Focus Key Requirements
9 Performance Evaluation Monitoring, measuring, and analyzing the performance of the AIMS and AI systems. This includes:
– Conducting Internal Audits.
– Management Review of the AIMS.
10 Improvement Take action to address nonconformities and continually improve the suitability, adequacy, and effectiveness of the AIMS.

Annex A (Controls)

While not a main clause, Annex A is a normative (mandatory) part of the standard. It provides a reference set of 39 specific control objectives and controls to mitigate AI-related risks, such as:

  • Controls for bias mitigation and fairness.
  • Controls related to transparency, explainability, and traceability.
  • Controls for the AI system lifecycle and data management.
  • Controls for third-party and customer relationships.

Documents needed for ISO 42001 certification audit

The certification audit for ISO/IEC 42001:2023 (Artificial Intelligence Management System – AIMS) requires an organization to provide documented information and records to demonstrate compliance with the standard’s requirements (Clauses 4-10) and its specific controls (Annex A).

The documentation falls into two main categories: Policies and Procedures (to show how you manage AI) and Records (to show proof that you are doing it).

1. Mandatory Policies and Procedures (Clauses 4-8)

 

These are the core documents that define your AIMS:

ISO Clause Required Documented Information (Policies/Procedures) Key Content
4 (Context) Scope of the AIMS Defines the boundaries, AI systems, and processes included in the AIMS.
5 (Leadership) AI Policy Top management’s commitment, goals, and principles for responsible AI.
6 (Planning) AI Risk Assessment Methodology Defines how AI risks (e.g., security, bias, societal impact) are identified, analyzed, and evaluated.
6 (Planning) AI System Impact Assessment (AIIA) Procedure Defines the process for assessing the impacts of AI systems on individuals and society.
6 (Planning) Statement of Applicability (SoA) Lists all controls from Annex A, states whether each control is applied or not, and provides a clear justification for its inclusion or exclusion.
8 (Operation) AI System Life Cycle Procedures Defines the processes for the development, testing, deployment, and monitoring of AI systems.
8 (Operation) Procedures for AI Data Management Covers data governance, provenance, quality, and bias mitigation in data used for AI.
10 (Improvement) Nonconformity and Corrective Action Procedure Defines how failures, incidents, or non-compliance are reported, investigated, and corrected.

2. Mandatory Records (Evidence of Implementation)

 

These records provide evidence that the policies and procedures are being followed:

ISO Clause Required Records (Evidence of Implementation) Evidence Focus
4 (Context) List of Interested Parties and their needs/expectations. Stakeholder input on AI risks and ethical concerns.
5 (Leadership) Roles, Responsibilities, and Authorities Documents who is accountable for AI systems and the AIMS.
6 (Planning) AI Risk Assessment Report & Risk Treatment Plan Records of identified risks, their scores, and the controls chosen to treat them.
6 (Planning) AI Objectives and Plans Records of measurable AI objectives and the plans to achieve them.
7 (Support) Records of Competence and Training Proof that personnel involved with AI systems are adequately trained on the AIMS, ethics, and relevant skills.
9 (Evaluation) Internal Audit Reports Records of planned and executed internal audits and their findings.
9 (Evaluation) Management Review Minutes Records of the top management review meeting, inputs, and decisions.
10 (Improvement) Records of Nonconformities and Corrective Actions Proof that issues have been addressed and the effectiveness of corrective actions was reviewed.

Crucial AI-Specific Records

 

To address the unique demands of AI, be prepared to present detailed documentation for:

  • AI System Impact Assessments (AIIA) Reports for all in-scope AI systems.
  • Logs and Records demonstrating compliance with transparency and explainability requirements (e.g., records of why an AI system made a high-risk decision).
  • Evidence of monitoring for bias, fairness, and model drift in deployed AI systems.
  • Supplier/Third-Party Agreements that extend AIMS controls to external parties providing AI components or services.

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