100% Pass Quiz 2026 GAICC ISO-IEC-42001-Foundation–Professional Valid Test Objectives

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

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

Section

Weight

Objectives

Topic 1: Core Components of the Artificial Intelligence Management System (AIMS)

40%

- AI Risk and Impact Assessments

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

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

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

- AI Policy and Organizational Values

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

- Performance Evaluation and Continual Improvement

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

- Operational Controls and Documentation Requirements

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

Topic 2: Fundamentals of AI Governance and the ISO/IEC 42001 Framework

40%

- Structure and Clauses of ISO/IEC 42001

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

- Relationship Between ISO/IEC 42001 and Other Management Standards

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

- Risk-Based Thinking in AI Governance

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

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

Topic 3: Responsible AI, Ethics, and Stakeholder Awareness

20%

- Stakeholder Roles in AI Governance

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

- Ethical Principles of Responsible AI

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

- Transparency and Explainability in AI Systems

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

- Communication, Stakeholder Engagement, and Trust

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

>> ISO-IEC-42001-Foundation Valid Test Objectives <<

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

NEW QUESTION # 28
A telecommunications operator is choosing between two architectures for a customer-service AI assistant.
Option A retrains a very large foundation model weekly on internal data; Option B fine-tunes a substantially smaller model monthly. Both meet functional accuracy requirements. The AIMS lead is asked how ISO/IEC
42001 treats environmental considerations when an organisation selects an AI design. Which response BEST reflects the standard ' s intent?

A. Environmental impact considerations apply solely to AI systems that perform climate-related functions such as emissions forecasting; for a customer service assistant the environmental dimension of architecture choice falls outside the relevant scope.
B. Environmental considerations sit outside the AIMS and belong with the corporate sustainability team, so the AI architecture decision should be driven purely by functional accuracy and time-to-market without consideration of energy or compute footprint.
C. Environmental impact is among the considerations the AI System Impact Assessment is expected to address, so the operator should evaluate the energy and compute footprint of each option alongside functional performance before approving an architecture.
D. Environmental impact should be evaluated by the cloud provider rather than the operator, since the provider operates the underlying infrastructure and is better placed than the operator to compare the relative carbon profiles of competing architectures.

Answer: C

Explanation:
Comprehensive and Detailed Explanation From [GAICC ISO/IEC 42001/Course Guide/topics]:
ISO/IEC 42001 establishes an operational framework that integrates societal and environmental dimensions directly into the engineering and procurement lifecycle of AI systems. Under Clause 6.1.4 (AI System Impact Assessment) and the reference controls in Annex A (specifically domain A.6 regarding resource management and AI lifecycle governance), organizations must assess the broader ramifications of system deployment. This includes evaluating the compute intensity, power consumption, data storage volume, and resulting carbon footprint of competing model designs. An organization cannot abdicate environmental due diligence to a hyperscaler or corporate sustainability committee; the AIMS requires technical decision-makers to evaluate whether excessive computational consumption is disproportionate to functional performance gains.
Comparing retraining cadences and model parameter scale against sustainable resource objectives directly supports responsible AI development and lifecycle optimization.
Reference: ISO/IEC 42001:2023 Clause 6.1.4 (AI system impact assessment); Annex A.6; GAICC Foundation Module 7 (AI Impact Assessment & Societal Considerations).

NEW QUESTION # 29
A foundation case workshop closes with a scenario in which a charity is about to launch an AI tool that helps caseworkers prioritise vulnerable-client outreach. The AIMS lead is asked which set of considerations the launch checklist should reflect, drawing on the responsible-AI principles in ISO/IEC 42001 Annex B together with the relevant management-system clauses. Which response BEST integrates the standard ' s expectations for a deployment of this kind?

A. Complete an AI System Impact Assessment under Clause 6.1.4 covering fairness, transparency, human oversight, privacy, and safety considerations, define acceptance criteria, assign role responsibilities, and gain documented approval before launch.
B. Postpone any structured impact assessment until after the first quarter of operational data has been gathered, on the basis that the charity will be better placed to evaluate impact once real-world caseworker usage patterns and outcome distributions have been observed.
C. Verify the model ' s predictive accuracy meets the agreed target, document the result in a one-page summary signed by the head of technology, and proceed to launch without further reference to other responsible-AI considerations for this charitable use case.
D. Confirm that the vendor has provided a model card, treat that document as a complete responsible-AI record for the deployment, and rely on the vendor ' s representations rather than performing an internal review of the model ' s fitness for the charity ' s specific population of clients.

Answer: A

Explanation:
Comprehensive and Detailed Explanation From [GAICC ISO/IEC 42001/Course Guide/topics]:
Deploying an algorithm that affects vulnerable individuals requires an end-to-end integration of risk treatment, ethical safeguards, and management system governance. Clause 6.1.4 (AI system impact assessment) mandates that organizations establish, implement, and maintain processes for assessing the potential impacts of the AI system on individuals, groups, and society. In a high-consequence charitable triage scenario, impact assessment cannot be deferred until post-deployment or reduced solely to verifying statistical accuracy. The assessment must evaluate core responsible AI principles outlined in Annex B, including fairness across marginalized subgroups, human oversight to ensure caseworkers retain override discretion, transparency regarding prioritization criteria, data privacy, and unintended harms. Deploying entities must define objective acceptance thresholds, formally assign operational monitoring responsibilities under Clause
5.3, and obtain sign-off before operational launch.
Reference: ISO/IEC 42001:2023 Clause 6.1.4 (AI system impact assessment); Annex B (Guidance on responsible AI principles); GAICC Foundation Module 7 (AI Impact Assessment & Lifecycle Governance).

NEW QUESTION # 30
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 an authoritative third party that assesses and formally recognises the competence of certification bodies to audit against standards such as ISO/IEC 42001.
B. 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.
C. 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.
D. An accreditation body is the publisher of an ISO standard, responsible for drafting the requirements text, maintaining revisions, and updating the harmonised structure terms.

Answer: A

Explanation:
Comprehensive and Detailed Explanation From [GAICC ISO/IEC 42001/Course Guide/topics]:
In the global conformity assessment hierarchy governed by the International Accreditation Forum (IAF) and ISO/IEC 17011, there is a distinct structural separation between certification and accreditation. Organizations seeking to validate their AIMS undergo a certification audit performed by a Certification Body (Conformity Assessment Body). In turn, the competence, impartiality, and procedural integrity of the Certification Body are evaluated, formally approved, and surveilled by an authoritative Accreditation Body (such as UKAS in the UK, ANAB in the United States, or DAkkS in Germany). Accreditation acts as the authoritative mechanism that validates certification bodies, ensuring mutual recognition of ISO/IEC 42001 certificates across global jurisdictions. Accreditation bodies do not provide consulting services, conduct internal enterprise audits, or author the underlying international standards (which is the purview of ISO/IEC JTC 1/SC 42).
Reference: ISO/IEC 17011; ISO/IEC 17021-1; GAICC Foundation Module 2 (The Global Conformity Assessment Infrastructure).

NEW QUESTION # 31
A foundation candidate is asked to identify which attributes an AI policy must include to satisfy ISO/IEC
42001 Clause 5.2. The candidate is given four short summary statements about an AI policy drafted by a logistics company that uses route-optimisation and demand-forecast models. The policy is one printed page, signed by the chief executive, and posted on the staff intranet. Which summary BEST reflects the minimum attributes Clause 5.2 requires of a documented AI policy?

A. The policy promises to obtain ISO/IEC 42001 certification within twelve months, names the chosen certification body, and commits the chief executive to attend each surveillance audit in person to answer auditor questions.
B. The policy lists every AI model the organisation operates, names the data scientist accountable for each model, and specifies the exact retraining cadence in months for the algorithms used by the logistics planning team.
C. The policy is appropriate to the organisation ' s purpose, provides a framework for AI objectives, commits to satisfying applicable requirements, and commits to continual improvement of the AI management system.
D. The policy mirrors the wording of the EU AI Act in full, copies the relevant sections of the local privacy statute verbatim, and republishes the text of Annex A controls so staff have one combined reference document.

Answer: C

Explanation:
Comprehensive and Detailed Explanation From [GAICC ISO/IEC 42001/Course Guide/topics]:
Clause 5.2 (AI Policy) defines four mandatory statutory criteria that top management must satisfy when formulating the documented AI policy. Specifically, the AI policy must: (a) be appropriate to the purpose and context of the organization; (b) provide a structured framework for setting AI objectives; (c) include a formal commitment to satisfy applicable legal, statutory, regulatory, and contractual requirements; and (d) include a clear commitment to the continual improvement of the AI management system. The policy is an executive- level strategic commitment rather than a granular technical asset inventory or model configuration logbook.
Prescribing operational model parameters, copying external legislation verbatim, or committing to prospective audit timelines conflates operational procedures with core leadership governance policies.
Reference: ISO/IEC 42001:2023 Clause 5.2 (AI policy); GAICC Foundation Module 5 (Policy Formulation & Strategic Intent).

NEW QUESTION # 32
A foundation candidate is asked to draft the agenda for a hospital network ' s first AIMS management review, scheduled six months after policy adoption. The chief executive will chair, and the appointed AIMS reporting officer will present. The case workshop offers four candidate agendas. Which agenda BEST reflects the leadership and review expectations of ISO/IEC 42001 Clauses 5 and 9.3 at this stage of the management system ' s life cycle?

A. A single-item agenda focused on reaffirming the AI policy signature, with no review of AIMS performance indicators, risk and impact-assessment status, or resource adequacy at this early stage of the management system ' s operating life cycle.
B. An agenda centred on vendor-management updates from the procurement team, with limited coverage of internal AIMS performance, risk-assessment outputs, impact-assessment status, or the suitability of the AI policy at six months in.
C. An agenda dominated by detailed technical model-architecture walkthroughs delivered by the data science team, with little time devoted to governance, risk treatment, or the decisions top management is expected to make at the close of the review.
D. An agenda that reviews AIMS performance, status of AI risk and impact assessments, audit and monitoring outputs, the continuing suitability of the AI policy, and resource and improvement decisions for top-management action.

Answer: D

Explanation:
Comprehensive and Detailed Explanation From [GAICC ISO/IEC 42001/Course Guide/topics]:
Clause 9.3 (Management review) requires top management to review the organization ' s AI management system at planned intervals to ensure its continuing suitability, adequacy, and effectiveness. The standard sets out mandatory review inputs, which include: status of actions from previous reviews; changes in internal and external context; fulfillment of AI objectives; information on AIMS performance (including nonconformities, monitoring and measurement results, and audit findings); outputs from AI risk assessments and AI System Impact Assessments (Clause 6.1.4); and resource adequacy. Furthermore, the review must culminate in documented outputs regarding improvement opportunities and resource allocation decisions. An agenda skewed exclusively toward technical engineering minutiae, narrow supplier updates, or superficial policy reaffirmation fails to satisfy the comprehensive governance oversight mandated under Clause 9.3 and Clause
5.1.
Reference: ISO/IEC 42001:2023 Clause 9.3 (Management review); Clause 5.1; GAICC Foundation Module 9 (Performance Evaluation & Management Review).

NEW QUESTION # 33
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