ISO 42001 AI Management System Internal Audit Checklist - Structured Level
This checklist assesses whether the organization has moved beyond initial AI awareness and established a structured Artificial Intelligence Management System (AIMS). At this maturity level, the organization should have: Formal AI governance structures, Defined AI lifecycle management processes, Documented risk assessment and treatment methods, Controlled AI development and deployment processes, Defined monitoring and improvement practices. This level is intended for organizations that already use AI solutions and want to establish consistent, repeatable governance.
This checklist template is designed for logistics, manufacturing, service companies and focuses on Basic information, AI Governance Structure and Leadership, AI Objectives and Planning.
What This Template Covers
Use this template to review Basic information, AI Governance Structure and Leadership, AI Objectives and Planning with a structured format that supports consistent follow-up and faster decision-making.
- Basic information
- AI Governance Structure and Leadership
- AI Objectives and Planning
Why This Version Is Different
Unlike generic templates, this version is tailored to the ai system deployment category, the Structured / Intermediate maturity level, and the workflow of logistics, manufacturing, service companies.
Template Questions
Showing first 15 rows
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Basic information |
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Audit date |
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Name of the auditors |
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Audited department |
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Names of the interviewed employees |
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#. Attachments |
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Section 1 - AI Governance Structure & Leadership |
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1. Has the organization established a formal AI governance framework defining how AI systems are managed?
Clauses:
Clause 5.1 - Leadership and commitment. Clause 5.3 - Roles, responsibilities and authorities. AI governance is managed through defined processes rather than individual decisions by separate departments.
Recommendations:
Create an AI governance framework covering decision-making, approvals, ownership, risk review, and monitoring responsibilities.
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2. Are AI system owners formally assigned for all significant AI applications?
Clauses:
Clause 5.3 - Roles, responsibilities and authorities. Each AI system has a responsible owner accountable for performance, risks, and lifecycle decisions.
Recommendations:
Assign ownership based on business impact and operational responsibility.
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3. Are responsibilities between business, IT, security, data, and compliance teams clearly defined?
Clauses:
Clause 5.3 - Roles, responsibilities and authorities. Different functions understand their responsibilities in AI development, deployment, monitoring, and risk management.
Recommendations:
Create an AI responsibility matrix (RACI) covering the AI lifecycle.
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4. Are AI governance requirements integrated into organizational processes and decision-making?
Clauses:
Clause 5.1 - Leadership and commitment. Clause 6.1 - Actions to address risks and opportunities. AI governance is part of normal business management rather than a separate activity.
Recommendations:
Include AI reviews in project approval, investment decisions, and management reviews.
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5. Has the organization established an AI policy appropriate to its AI activities and risks?
Clauses:
Clause 5.2 - AI policy. The organization has documented principles and commitments for responsible AI use.
Recommendations:
Update the AI policy to include accountability, transparency, risk management, security, and continual improvement.
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Section 2 - AI Objectives & Planning |
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6. Are AI objectives defined and aligned with organizational strategy?
Clauses:
Clause 6.2 - AI objectives and planning to achieve them. AI adoption supports measurable business outcomes.
Recommendations:
Define objectives such as productivity improvement, quality enhancement, risk reduction, or customer value creation.
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7. Are resources required to achieve AI objectives identified and planned?
Clauses:
Clause 6.2 - AI objectives and planning. Clause 7.1 - Resources. The organization considers people, technology, data, and financial resources needed for successful AI implementation.
Recommendations:
Include AI capability requirements in business planning.
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30 total questions
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