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

Section	Weight	Objectives
Topic 1: Responsible AI, Ethics, and Stakeholder Awareness	20%	- Ethical principles and AI responsibility 1. Roles and responsibilities of AI providers, producers and customers 2. Stakeholder engagement and transparency 3. Fairness, explainability and oversight mechanisms
Topic 2: Core Components of the Artificial Intelligence Management System (AIMS)	40%	- Key clauses and requirements of ISO/IEC 42001 1. Leadership, planning and support 2. Operation, performance evaluation and improvement
Topic 3: Fundamentals of AI Governance and the ISO/IEC 42001 Framework	40%	- Relationship between AIMS and organizational context - Basic concepts of AI and AI Management Systems (AIMS) 1. AI system lifecycle concepts 2. Terminology from ISO/IEC 22989 and ISO/IEC 42001 3. Purpose, scope and structure of ISO/IEC 42001:2023

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GAICC ISO/IEC 42001 Foundation Sample Questions (Q14-Q19):

NEW QUESTION # 14
A documentation lead is preparing a one-page reference for new joiners that names the four annexes of ISO
/IEC 42001 and their purpose. She wants the description that aligns with GAICC Foundation Module 3.
Which option BEST matches the role of each annex in the standard?

A. Annex A maps ISO/IEC 42001 to ISO 9001 directly; Annex B is a vocabulary appendix; Annex C is a sample Statement of Applicability; Annex D is a glossary of regional AI regulations.
B. Annex A is a list of accredited certification bodies; Annex B is a Stage 2 audit checklist; Annex C is a Statement of Applicability template; Annex D is a financial impact assessment model.
C. Annex A is the reference control set; Annex B is implementation guidance; Annex C catalogues AI- related objectives and risk sources; Annex D shows integration with other management system standards.
D. Annex A is a published list of certified consultants; Annex B is the official EU AI Act mapping; Annex C is a sample AI policy template; Annex D is the standard ' s revision history log.

Answer: C

Explanation:
Comprehensive and Detailed Explanation From [GAICC ISO/IEC 42001/Course Guide/topics]:
ISO/IEC 42001 contains four structured annexes designed to assist organizations in architecting and operationalizing their AIMS. Annex A provides the normative reference control set containing 38 control objectives and controls divided into domains (A.2 through A.10). Annex B provides informative guidance for implementing these controls, detailing best practices for human oversight, transparency, and data governance.
Annex C catalogues potential AI-related organizational objectives, use cases, and distinct risk sources (such as algorithmic bias, safety failures, and intellectual property infringement). Finally, Annex D provides informative mapping and integration guidance, illustrating how ISO/IEC 42001 aligns with and complements other established management system standards like ISO 9001 (Quality) and ISO/IEC 27001 (Information Security).
Reference: ISO/IEC 42001:2023 Annexes A, B, C, and D; GAICC Foundation Module 3 (Standard Architecture and Annex Structural Roles).

NEW QUESTION # 15
A start-up founder argues that ISO/IEC 42001 is irrelevant to her company because it neither develops AI models nor sells AI products-it merely uses a third-party generative AI assistant to draft customer support replies. The compliance lead disagrees and points to the standard ' s scope as described in the GAICC Foundation materials. Which statement BEST captures who ISO/IEC 42001 is intended for?

A. Public-sector bodies subject to AI legislation, since voluntary management system standards are intended for regulated entities rather than commercial start-ups.
B. Any organisation that develops, provides, or uses AI systems, irrespective of size, sector, or AI maturity, including those that consume AI through third-party tools.
C. Organisations that build and train their own AI models from scratch, since the standard targets AI developers rather than downstream users of third-party vendor tools.
D. Enterprises above a defined revenue threshold, since the cost and complexity of an AI management system is disproportionate for smaller firms or early-stage start-ups.

Answer: B

Explanation:
Comprehensive and Detailed Explanation From [GAICC ISO/IEC 42001/Course Guide/topics]:
Clause 1 (Scope) of ISO/IEC 42001 specifies that the standard is universally applicable to any organization, regardless of its size, nature, sector, or operational maturity, that develops, provides, or uses products or services that utilize artificial intelligence systems. The standard explicitly rejects the premise that AI governance is exclusively relevant to foundational frontier model builders or commercial software vendors.
Downstream deployers and end-users of third-party commercial tools-such as enterprises leveraging third- party large language models for customer engagement-introduce operational, legal, privacy, and reputational risks into their operational environments. Consequently, organizations acting purely as AI users must establish governance oversight over tool selection, acceptable use policies, prompt data confidentiality, operational monitoring, and vendor relationship controls governed under Annex A (specifically domain A.9).
The standard's requirements are scalable and proportionate to organizational context and risk exposure rather than headcount or development footprint.
Reference: ISO/IEC 42001:2023 Clause 1 (Scope); GAICC Foundation Module 1 (The Purpose, Applicability, and Reach of ISO/IEC 42001).

NEW QUESTION # 16
A retail bank ' s procurement team has begun receiving requests from enterprise clients asking the bank to demonstrate how it governs the AI models used in credit decisioning. The Chief Risk Officer wants a single, internationally recognised framework that addresses AI specifically-not just general quality or information- security controls-and that can be independently certified. Which standard BEST fits this need under the GAICC Foundation view of why ISO/IEC 42001 was published?

A. ISO/IEC 42001, the first international management system standard dedicated to artificial intelligence and capable of third-party certification.
B. ISO/IEC 27001, the information security management system standard, which fully addresses AI governance through its existing Annex A control set.
C. The OECD AI Principles, which provide an internationally agreed policy framework for trustworthy AI and a basis for third-party certification.
D. ISO 9001, the international quality management system standard, which already covers AI quality assurance for regulated banking workloads.

Answer: A

Explanation:
Comprehensive and Detailed Explanation From [GAICC ISO/IEC 42001/Course Guide/topics]:
ISO/IEC 42001 was developed jointly by ISO and IEC (through JTC 1/SC 42) to establish the world's first certifiable Artificial Intelligence Management System (AIMS) standard. While ISO 9001 addresses overarching quality processes and ISO/IEC 27001 governs information security, neither framework provides specialized, auditable criteria for unique AI risks, including model hallucinations, statistical bias, algorithmic drift, lack of explainability, data poisoning, and autonomous decision opacity. Furthermore, while the OECD AI Principles define high-level global policy benchmarks for trustworthy AI, they are non-binding policy guidance that lack formal conformity assessment specifications. ISO/IEC 42001 fills this gap by delivering an auditable, Harmonized Structure management system against which accredited conformity assessment bodies can perform independent third-party audits and issue formal organizational certification.
Reference: ISO/IEC 42001:2023 Scope; GAICC Foundation Module 1 (The Emergence & Global Role of ISO
/IEC 42001).

NEW QUESTION # 17
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 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.
B. 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.
C. 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.
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: B

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 # 18
A retail bank is preparing to deploy a new AI tool that ranks loan applicants by predicted creditworthiness.
The model was trained on five years of historical lending data drawn from a single metropolitan region.
Before go-live, the AIMS lead must propose a fairness check consistent with ISO/IEC 42001 expectations on responsible AI. Which approach BEST reflects the standard ' s intent for bias detection during AI system impact assessment?

A. Wait for the first quarter of live decisions to accumulate, then run a retrospective fairness analysis on actual decision outcomes, since live data is more representative than any test data the bank could realistically assemble in a development environment.
B. Document an assumption in the AI System Impact Assessment that historical lending data is representative of the wider applicant population and proceed to deployment, with no quantitative fairness testing of model outputs prior to release.
C. Evaluate predicted-outcome disparities across protected groups using pre-defined fairness metrics, document the results in the AI System Impact Assessment, and confirm acceptance criteria are met before approving the model for deployment.
D. Restrict the deployment to a single business unit for the first month, with no formal pre-launch fairness testing, and rely on customer complaints to surface unfair outcomes for downstream investigation by the responsible model team.

Answer: C

Explanation:
Comprehensive and Detailed Explanation From [GAICC ISO/IEC 42001/Course Guide/topics]:
In algorithmic lending, bias poses significant legal, regulatory, and ethical risks. Under ISO/IEC 42001 Clause 6.1.4 and Annex A.7 (Data for AI systems), organizations deploying consequential decision-making tools must institute rigorous pre-deployment evaluation processes. Because historical datasets frequently encode institutional disparities and regional sampling imbalances, the organization must establish clear, quantifiable fairness acceptance criteria (such as disparate impact ratios, demographic parity, or equalized odds metrics). Model performance across relevant demographic and protected classes must be measured against these predefined thresholds. The findings, trade-offs, and mitigation strategies must be documented within the AI System Impact Assessment record before production release. Deferring testing until post-launch complaints emerge or relying on unverified assumptions violates the core risk prevention and impact governance mandates of the standard.
Reference: ISO/IEC 42001:2023 Clause 6.1.4; Annex B.3 (Fairness); Control Domain A.7; GAICC Foundation Module 6 (Algorithmic Fairness and Quantitative Evaluation).

NEW QUESTION # 19
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