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GAICC ISO-IEC-42001-Foundation Exam Syllabus Topics:

Section	Weight	Objectives
Core Components of the Artificial Intelligence Management System (AIMS)	40%	- Performance Evaluation and Continual Improvement 1. Internal reviews 2. AI system monitoring 3. Corrective actions 4. Continual improvement through the PDCA cycle - Operational Controls and Documentation Requirements 1. AI model change records 2. AI incident logs and operational documentation 3. Data governance procedures - AI Policy and Organizational Values 1. Purpose and role of an AI policy 2. Integration of AI risk management into organizational values 3. Leadership commitment to fairness and transparency - Main Requirements of ISO/IEC 42001 Clauses 4–10 1. Context of the organization 2. Leadership 3. Support 4. Operation 5. Performance evaluation 6. Planning 7. Improvement - AI Risk and Impact Assessments 1. AI risk assessment concepts 2. AI System Impact Assessment (AI-SIA) 3. AI impact assessment documentation
Responsible AI, Ethics, and Stakeholder Awareness	20%	- Transparency and Explainability in AI Systems 1. Transparency in AI systems 2. Explainability of AI decisions 3. Understandable AI decisions for users and regulators - Ethical Principles of Responsible AI 1. Fairness and non-discrimination 2. Accountability 3. Privacy 4. Human oversight - Communication, Stakeholder Engagement, and Trust 1. Building trust through stakeholder engagement 2. Responsible AI policies 3. AI ethics statements 4. Public disclosures and stakeholder communication - Stakeholder Roles in AI Governance 1. External stakeholders Customers Regulators Society 2. Internal stakeholders Organizational leadership AI developers Compliance teams
Fundamentals of AI Governance and the ISO/IEC 42001 Framework	40%	- Structure and Clauses of ISO/IEC 42001 1. Structure and sequence of ISO/IEC 42001 2. Plan-Do-Check-Act (PDCA) cycle 3. Requirements covered by Clauses 4–10 - Relationship Between ISO/IEC 42001 and Other Management Standards 1. Relationship with ISO/IEC 27701 2. Relationship with ISO/IEC 27001 3. Relationship with ISO 9001 - Key Terms and Definitions Related to AI Governance 1. Artificial Intelligence Management System (AIMS) 2. Accountability, bias, and transparency 3. AI lifecycle and continual improvement - Risk-Based Thinking in AI Governance 1. Integration of AI risks with organizational objectives 2. AI risk assessment and mitigation 3. Identification of AI-related risks - Purpose and Scope of ISO/IEC 42001 1. Organizational adoption of AI governance frameworks 2. Purpose and objectives of the Artificial Intelligence Management System (AIMS) 3. Alignment with ethical AI principles and sustainable digital transformation

Section

Weight

Objectives

Core Components of the Artificial Intelligence Management System (AIMS)

40%

- Performance Evaluation and Continual Improvement

1. Internal reviews
2. AI system monitoring
3. Corrective actions
4. Continual improvement through the PDCA cycle

- Operational Controls and Documentation Requirements

1. AI model change records
2. AI incident logs and operational documentation
3. Data governance procedures

- AI Policy and Organizational Values

1. Purpose and role of an AI policy
2. Integration of AI risk management into organizational values
3. Leadership commitment to fairness and transparency

- Main Requirements of ISO/IEC 42001 Clauses 4–10

1. Context of the organization
2. Leadership
3. Support
4. Operation
5. Performance evaluation
6. Planning
7. Improvement

- AI Risk and Impact Assessments

1. AI risk assessment concepts
2. AI System Impact Assessment (AI-SIA)
3. AI impact assessment documentation

Responsible AI, Ethics, and Stakeholder Awareness

20%

- Transparency and Explainability in AI Systems

1. Transparency in AI systems
2. Explainability of AI decisions
3. Understandable AI decisions for users and regulators

- Ethical Principles of Responsible AI

1. Fairness and non-discrimination
2. Accountability
3. Privacy
4. Human oversight

- Communication, Stakeholder Engagement, and Trust

1. Building trust through stakeholder engagement
2. Responsible AI policies
3. AI ethics statements
4. Public disclosures and stakeholder communication

- Stakeholder Roles in AI Governance

1. External stakeholders
- Customers
- Regulators
- Society
2. Internal stakeholders
- Organizational leadership
- AI developers
- Compliance teams

Fundamentals of AI Governance and the ISO/IEC 42001 Framework

40%

- Structure and Clauses of ISO/IEC 42001

1. Structure and sequence of ISO/IEC 42001
2. Plan-Do-Check-Act (PDCA) cycle
3. Requirements covered by Clauses 4–10

- Relationship Between ISO/IEC 42001 and Other Management Standards

1. Relationship with ISO/IEC 27701
2. Relationship with ISO/IEC 27001
3. Relationship with ISO 9001

- Key Terms and Definitions Related to AI Governance

1. Artificial Intelligence Management System (AIMS)
2. Accountability, bias, and transparency
3. AI lifecycle and continual improvement

- Risk-Based Thinking in AI Governance

1. Integration of AI risks with organizational objectives
2. AI risk assessment and mitigation
3. Identification of AI-related risks

- Purpose and Scope of ISO/IEC 42001

1. Organizational adoption of AI governance frameworks
2. Purpose and objectives of the Artificial Intelligence Management System (AIMS)
3. Alignment with ethical AI principles and sustainable digital transformation

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GAICC ISO/IEC 42001 Foundation Sample Questions (Q13-Q18):

NEW QUESTION # 13
A compliance manager is preparing a slide for the leadership team to explain the difference between accreditation and certification in the ISO/IEC 42001 ecosystem. She wants a one-sentence working definition of an accreditation body that aligns with GAICC Foundation Module 2. Which option is the BEST fit?

A. An accreditation body is the internal audit function within an organisation that reviews the AIMS against ISO/IEC 42001 before any external certification audit is conducted.
B. An accreditation body is an authoritative third party that assesses and formally recognises the competence of certification bodies to audit against standards such as ISO/IEC 42001.
C. An accreditation body is the publisher of an ISO standard, responsible for drafting the requirements text, maintaining revisions, and updating the harmonised structure terms.
D. An accreditation body is the consulting firm engaged by an organisation to help draft its AI policy, conduct gap analyses, and prepare evidence packs for a Stage 1 audit.

Answer: B

NEW QUESTION # 14
A new compliance analyst is reading ISO/IEC 42001 for the first time and asks her mentor what the acronym ' AIMS ' stands for in the context of this standard. According to Clause 3 and GAICC Foundation Module 3, which option provides the correct expansion?

A. AI Monitoring and Surveillance-the runtime telemetry layer that watches deployed AI models for performance drift, anomalous outputs, and integrity breaches.
B. AI Management System-the set of interrelated elements an organisation uses to establish policies and objectives for its AI activities and the processes to achieve them.
C. Audit Integrity Maintenance Schedule-the calendar that governs internal audit cadence, surveillance audits, and recertification audits across a three-year cycle.
D. AI Impact Mitigation Strategy-the documented plan describing how an organisation will treat residual AI risks identified through impact assessment activities.

Answer: B

Explanation:
Comprehensive and Detailed Explanation From [GAICC ISO/IEC 42001/Course Guide/topics]:
In accordance with ISO/IEC 42001 Clause 3 (Terms and definitions) and the Harmonized Structure common to all modern ISO management system standards, the acronym " AIMS " formally stands for " Artificial Intelligence Management System. " Clause 3 defines a management system as a set of interrelated or interacting elements of an organization to establish policies and objectives, as well as processes to achieve those objectives. Therefore, the AIMS encompasses the governance framework, policies, structural controls, operational lifecycles, risk management methodologies, impact assessment mechanisms, and continuous improvement loops established to direct, govern, and control an entity's AI-related undertakings. It must not be conflated with point-in-time runtime telemetry platforms (AI monitoring), risk treatment blueprints, or audit scheduling timelines.
Reference: ISO/IEC 42001:2023 Clause 3.1; GAICC Foundation Module 3 (Vocabulary, Concepts, and Structural Frameworks).
Batch 2: Questions 11 to 20

NEW QUESTION # 15
An IT director is finalising the certification scope statement for his organisation ' s AIMS. He has been told that ISO/IEC 42001 is built on the Harmonized Structure used by other ISO management system standards.
According to GAICC Foundation Module 2, which clauses of ISO/IEC 42001 contain the auditable management system requirements?

A. Clauses 1, 2, and 3, which together set scope, normative references, and terms-the binding requirements that an audit team checks for conformity.
B. Clause 6 by itself, since it covers planning, risk assessment, and AI System Impact Assessment, which are the AI-specific elements that auditors evaluate.
C. Clauses 4 through 10, which carry the management system requirements that an external audit assesses for conformity against the standard.
D. Annexes A, B, C, and D, which are the principal sources of audit findings during a Stage 2 certification audit against an ISO management system standard.

Answer: C

Explanation:
Comprehensive and Detailed Explanation From [GAICC ISO/IEC 42001/Course Guide/topics]:
Like all modern ISO management system standards developed under ISO/IEC Directives Part 1 (such as ISO
9001, ISO/IEC 27001, and ISO 14001), ISO/IEC 42001 utilizes the standardized Harmonized Structure (formerly High-Level Structure / Annex SL). Within this universal structure, Clauses 1, 2, and 3 provide introductory context, normative references, and formal terminology definitions, respectively; they do not contain auditable management system requirements. The formal, auditable requirements against which external conformity assessment bodies evaluate an organization reside exclusively within Clauses 4 through
10: Context of the organization (4), Leadership (5), Planning (6), Support (7), Operation (8), Performance evaluation (9), and Improvement (10). While Annex A supplies reference controls assessed via the Statement of Applicability under Clause 6.1.3, the primary audit criteria are embedded within the core requirements of Clauses 4 through 10.
Reference: ISO/IEC 42001:2023 Clauses 4-10; GAICC Foundation Module 2 (Harmonized Structure & Standard Architecture).

NEW QUESTION # 16
A small insurance firm is performing its first context analysis under Clause 4.1 of ISO/IEC 42001. The compliance lead lists the factors the team should consider. Which item BEST illustrates an EXTERNAL issue relevant to the AIMS, consistent with GAICC Foundation Module 4?

A. The current inventory of AI models deployed in the underwriting platform and the technical debt accumulated within the firm ' s own internal data pipelines over time.
B. The composition of the firm ' s senior leadership team and the way responsibilities for AI initiatives are currently allocated across internal business units.
C. The forthcoming enforcement of regional AI legislation, such as the EU AI Act, and evolving public expectations about transparency in automated insurance decisions.
D. The firm ' s internal organisational culture and the maturity of its data engineering team, both of which influence how AI projects are scoped and delivered.

Answer: C

Explanation:
Comprehensive and Detailed Explanation From [GAICC ISO/IEC 42001/Course Guide/topics] :
Clause 4.1 (Understanding the organization and its context) mandates that an organization determine external and internal issues relevant to its purpose and that affect its ability to achieve the intended outcomes of its AI management system. The standard and GAICC Module 4 categorize external issues as factors arising outside the organization's operational perimeter. These encompass legal, statutory, regulatory, and contractual environments (such as the EU AI Act, regional AI safety frameworks, and insurance solvency regulations), economic and market dynamics, evolving technological advancements, and shifting societal and consumer expectations regarding algorithmic fairness and transparency. Conversely, workforce technical maturity, internal governance culture, technical debt in internal data pipelines, model inventories, and leadership committee structures represent internal issues. Recognizing external legislative and social pressures enables the entity to calibrate its compliance frameworks and risk appetites defensively before deploying algorithmic decision systems.
Reference: ISO/IEC 42001:2023 Clause 4.1 (Understanding the organization and its context); GAICC Foundation Module 4 (Context Analysis: External vs. Internal Drivers).

NEW QUESTION # 17
A travel platform plans to train a recommendation model on five years of customer booking history, including names, contact details, and trip itineraries. The data-protection officer raises concerns about training-data use.
The AI governance lead is asked how ISO/IEC 42001 treats the relationship between AI management and personal-data protection. Which response BEST reflects the standard ' s intent on privacy as a responsible-AI consideration?

A. Personal-data protection is a relevant input to the AI System Impact Assessment under Clause 6.1.4, and the AIMS should coordinate with applicable privacy obligations rather than treating data protection as a separate concern outside the scope of AI governance.
B. The AIMS should record an exception noting that training data is exempt from privacy review on grounds of model improvement, since pursuit of model accuracy provides a legitimate operational basis for the platform ' s use of historical booking information in training.
C. Personal-data protection sits entirely outside the AIMS because ISO/IEC 42001 governs AI systems and applicable privacy laws govern personal data, so the two regimes operate independently with no expectation of coordination across them.
D. The AI governance lead should remove privacy considerations from the AI System Impact Assessment scope and refer them to the privacy officer for a parallel assessment, with no formal linkage between the two assessment processes maintained within the AIMS records.

Answer: A

Explanation:
Comprehensive and Detailed Explanation From [GAICC ISO/IEC 42001/Course Guide/topics]:
ISO/IEC 42001 explicitly integrates data protection and privacy within its governance requirements. Under Clause 6.1.4 (AI system impact assessment), Clause 4.2 (Compliance obligations), and Annex A domain A.7 (Data for AI systems), privacy considerations are recognized as critical inputs to responsible AI management.
AI models trained on personal booking records present significant risks regarding data repurposing, re- identification, model inversion attacks, and non-compliance with data protection legislation (such as GDPR or regional equivalents). Rather than siloing AI governance from data privacy, the standard mandates active coordination. AI risk and impact assessments must evaluate privacy risks, enforce data minimization and pseudonymization, and document lawful processing baselines within the AIMS. Treating privacy as completely isolated from AI oversight or asserting unilateral exemptions for training activities directly violates the standard.
Reference: ISO/IEC 42001:2023 Clause 6.1.4; Control Domain A.7; Annex B.6 (Privacy); GAICC Foundation Module 7 (Data Protection, Privacy, and Model Lifecycle Governance).

NEW QUESTION # 18
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