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

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

Section

Weight

Objectives

Responsible AI, Ethics, and Stakeholder Awareness

20%

- Ethical Principles of Responsible AI

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

- Communication, Stakeholder Engagement, and Trust

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

- Transparency and Explainability in AI Systems

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

- Stakeholder Roles in AI Governance

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

Core Components of the Artificial Intelligence Management System (AIMS)

40%

- Performance Evaluation and Continual Improvement

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

- AI Risk and Impact Assessments

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

- Operational Controls and Documentation Requirements

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

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

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

- AI Policy and Organizational Values

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

Fundamentals of AI Governance and the ISO/IEC 42001 Framework

40%

- Risk-Based Thinking in AI Governance

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

- Relationship Between ISO/IEC 42001 and Other Management Standards

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

- Structure and Clauses of ISO/IEC 42001

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

- Key Terms and Definitions Related to AI Governance

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

- Purpose and Scope of ISO/IEC 42001

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

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GAICC ISO/IEC 42001 Foundation Sample Questions (Q28-Q33):

NEW QUESTION # 28
An education provider uses an AI plagiarism-detection tool supplied by a third-party vendor. A student is flagged incorrectly and appeals. The teacher refers the matter to the IT helpdesk, the helpdesk refers it to the procurement team, procurement refers it to the vendor, and the vendor refers it back to the institution. The student receives no clear response for several weeks. Which issue BEST reflects an accountability weakness under the responsible-AI principles in ISO/IEC 42001?

A. The student should be required to escalate the appeal through a formal external regulator rather than through the institution, as external regulators are better placed than internal staff to adjudicate AI- related complaints raised by individual learners.
B. No specific role inside the institution has been assigned responsibility for AI-system outcomes experienced by users, so the appeal cannot be addressed end to end-a gap inconsistent with the accountability principle and with Clause 5.3 role assignment.
C. Accountability is adequate because each team in the referral chain followed its own internal procedure, and procedural compliance by individual teams demonstrates that responsibility has been appropriately distributed across the institution.
D. The vendor should be considered solely accountable for the misclassification because the model was developed and trained externally, and the institution is therefore a passive consumer of the vendor ' s pre-built classification capability for student submissions.

Answer: B

Explanation:
Comprehensive and Detailed Explanation From [GAICC ISO/IEC 42001/Course Guide/topics]:
Accountability is a foundational pillar of ethical AI codified in ISO/IEC 42001 Annex B and enforced operationally through Clause 5.3 and Annex A controls (specifically A.2 on governance and A.9 on third- party relationships). Organizations deploying third-party AI systems cannot outsource accountability for end- user outcomes to commercial suppliers or diffuse responsibility across disjointed internal operational silos.
When an adverse or disputed decision occurs, the deploying entity must provide a defined recourse and human-oversight escalation pathway. The breakdown described illustrates a severe governance void: the lack of a designated role with clear authority to arbitrate model exceptions and resolve appeals. ISO/IEC 42001 mandates that organizations retain clear, end-to-end accountability for any operational system integrated into their service delivery pipelines.
Reference: ISO/IEC 42001:2023 Clause 5.3; Annex B.2 (Accountability); GAICC Foundation Module 6 (Responsible AI Principles & Organizational Accountability).

NEW QUESTION # 29
A government agency is establishing AIMS roles for its first ISO/IEC 42001 implementation. The chief information officer proposes that the AI Ethics Committee, made up of subject-matter experts drawn from across business units, owns AIMS performance reporting. The chief legal officer suggests the role sits with the procurement team because most AI tools are vendor-supplied. A foundation learner is asked what Clause
5.3 actually requires for the reporting-on-performance responsibility. Which response is BEST?

A. Reporting on AIMS performance should be split between the AI Ethics Committee and the procurement team on a shared-accountability basis, with each function presenting its segment of performance data to top management at separate review meetings each quarter.
B. Reporting on AIMS performance should sit with the procurement team, because vendor-supplied AI tools dominate the agency ' s portfolio and procurement holds the contractual levers needed to manage supplier obligations through purchase agreements.
C. Reporting on AIMS performance can rest with the AI Ethics Committee in its current advisory form, since cross-functional expertise is well placed to interpret AI risk and benefit signals across the agency ' s varied business areas and to provide nuanced commentary.
D. Top management must assign the responsibility and authority for reporting on the performance of the AIMS to a specific role or roles, and that assignment must be communicated within the organisation so the reporting line is unambiguous.

Answer: D

Explanation:
Comprehensive and Detailed Explanation From [GAICC ISO/IEC 42001/Course Guide/topics]:
Clause 5.3 (Organizational roles, responsibilities and authorities) requires top management to ensure that responsibilities and authorities for reporting on the performance of the AI management system to top management are formally assigned and communicated throughout the organization. The standard intentionally does not dictate the organizational title or functional department where this role must reside-it can be assigned to an AI Ethics Officer, Chief AI Officer, Head of Compliance, or a dedicated steering committee lead-provided the assignment is formally defined, backed by appropriate authority, and clearly communicated to eliminate ambiguity. Leaving governance reporting dispersed across uncoordinated committees or shared informally across multiple departments without clear ownership creates organizational blind spots, conflicting reporting streams, and accountability gaps.
Reference: ISO/IEC 42001:2023 Clause 5.3 (Organizational roles, responsibilities and authorities); GAICC Foundation Module 5 (Structural Roles, Reporting Lines, and Operational Authority).
Batch 4: Questions 31 to 40

NEW QUESTION # 30
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 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.
C. 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.
D. 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.

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 # 31
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. 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.
B. Clauses 4 through 10, which carry the management system requirements that an external audit assesses for conformity against the standard.
C. Clauses 1, 2, and 3, which together set scope, normative references, and terms-the binding requirements that an audit team checks for conformity.
D. Clause 6 by itself, since it covers planning, risk assessment, and AI System Impact Assessment, which are the AI-specific elements that auditors evaluate.

Answer: B

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 # 32
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 forthcoming enforcement of regional AI legislation, such as the EU AI Act, and evolving public expectations about transparency in automated insurance decisions.
B. 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.
C. The composition of the firm ' s senior leadership team and the way responsibilities for AI initiatives are currently allocated across internal business units.
D. 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.

Answer: A

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 # 33
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