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

Section	Weight	Objectives
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 - Communication, Stakeholder Engagement, and Trust 1. Public disclosures and stakeholder communication 2. AI ethics statements 3. Responsible AI policies 4. Building trust through stakeholder engagement - 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. Privacy 2. Accountability 3. Human oversight 4. Fairness and non-discrimination
Fundamentals of AI Governance and the ISO/IEC 42001 Framework	40%	- 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 - Key Terms and Definitions Related to AI Governance 1. Artificial Intelligence Management System (AIMS) 2. AI lifecycle and continual improvement 3. Accountability, bias, and transparency - Relationship Between ISO/IEC 42001 and Other Management Standards 1. Relationship with ISO/IEC 27701 2. Relationship with ISO 9001 3. Relationship with ISO/IEC 27001 - 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 - 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
Core Components of the Artificial Intelligence Management System (AIMS)	40%	- Main Requirements of ISO/IEC 42001 Clauses 4–10 1. Performance evaluation 2. Improvement 3. Support 4. Planning 5. Context of the organization 6. Operation 7. Leadership - Operational Controls and Documentation Requirements 1. AI incident logs and operational documentation 2. Data governance procedures 3. AI model change records - AI Policy and Organizational Values 1. Leadership commitment to fairness and transparency 2. Integration of AI risk management into organizational values 3. Purpose and role of an AI policy - Performance Evaluation and Continual Improvement 1. AI system monitoring 2. Continual improvement through the PDCA cycle 3. Internal reviews 4. Corrective actions - AI Risk and Impact Assessments 1. AI risk assessment concepts 2. AI System Impact Assessment (AI-SIA) 3. AI impact assessment documentation

Section

Weight

Objectives

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

- Communication, Stakeholder Engagement, and Trust

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

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

Fundamentals of AI Governance and the ISO/IEC 42001 Framework

40%

- 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

- Key Terms and Definitions Related to AI Governance

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

- Relationship Between ISO/IEC 42001 and Other Management Standards

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

- 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

- 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

Core Components of the Artificial Intelligence Management System (AIMS)

40%

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

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

- Operational Controls and Documentation Requirements

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

- AI Policy and Organizational Values

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

- Performance Evaluation and Continual Improvement

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

- AI Risk and Impact Assessments

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

>> New ISO-IEC-42001-Foundation Test Questions <<

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GAICC ISO/IEC 42001 Foundation Sample Questions (Q33-Q38):

NEW QUESTION # 33
A board director asks: ' Why should we invest in ISO/IEC 42001 certification rather than simply publishing an internal AI ethics statement? ' The Chief AI Officer responds by listing the drivers that motivated publication of the standard. Which option BEST summarises the main drivers behind ISO/IEC 42001 as presented in GAICC Foundation Module 1?

A. Pressure from professional indemnity insurers, who require ISO/IEC 42001 certification as a precondition for issuing technology errors-and-omissions policies to AI software vendors worldwide.
B. Converging regulatory, commercial, reputational, and operational pressures around AI-including new AI laws, procurement scrutiny, public AI failures, and consequential AI decisions.
C. A specific request from the World Trade Organization to harmonise tariff treatment for AI-enabled goods and services across the major trading blocs by the end of the year 2026.
D. A directive from the International Telecommunication Union requiring each member state to publish a national AI register before the end of 2026, with a binding regional reporting cycle.

Answer: B

Explanation:
Comprehensive and Detailed Explanation From [GAICC ISO/IEC 42001/Course Guide/topics]:
The inception and rapid global adoption of ISO/IEC 42001 are driven by the intersection of four critical operational forces: evolving legal compliance (such as the EU AI Act and emerging national frameworks), rigorous commercial procurement diligence, acute reputational risks stemming from publicized model failures, and the expanding delegation of high-stakes, consequential decisions to autonomous systems.
Informal corporate AI ethics statements lack enforceable verification, audit mechanisms, and systematic lifecycle controls, often inviting accusations of " ethics washing. " In contrast, ISO/IEC 42001 addresses these mounting industry pressures by codifying an internationally auditable standard. Organizations implement the standard to prove governance rigor to enterprise buyers, withstand regulatory audits, prevent systemic operational harms, and safeguard enterprise reputation through documented, verifiable conformity.
Reference: ISO/IEC 42001:2023 Introduction; GAICC Foundation Module 1 (Business & Regulatory Drivers for AI Governance).

NEW QUESTION # 34
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. 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.
B. 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.
C. 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.
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: A

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 # 35
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 1, 2, and 3, which together set scope, normative references, and terms-the binding requirements that an audit team checks for conformity.
C. Clauses 4 through 10, which carry the management system requirements that an external audit assesses for conformity against the standard.
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: 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 # 36
A logistics company has implemented an AI system that recommends staffing levels for warehouse shifts. The user interface shows each recommendation with an ' Approve ' button. In practice, shift managers approve every recommendation within seconds because the system rarely surfaces context, and the interface does not let managers see the inputs that drove the decision. Reviewing this for responsible-AI conformance, which observation BEST reflects the human-oversight principle from ISO/IEC 42001 Annex B?

A. Human oversight is not engaged here because shift staffing is a low-risk operational decision; Annex B
' s oversight principle applies primarily to high-risk AI systems such as those that affect safety or fundamental rights, so the interface design issue is immaterial.
B. The oversight is not meaningful because managers lack the information and context needed to challenge or override the recommendation, so the design provides the appearance of human control without the substance Annex B ' s human-oversight principle expects.
C. The approve-button workflow satisfies human-oversight expectations because a human is in the loop for every staffing decision, and the speed of approvals reflects the efficiency gains of well-designed AI tooling rather than a control weakness in the deployed interface.
D. Human oversight should be removed in favour of fully automated approvals on grounds of consistency, with sample audits performed monthly by the operations team to verify that the system ' s recommendations remain reasonable across the warehouse network over time.

Answer: B

Explanation:
Comprehensive and Detailed Explanation From [GAICC ISO/IEC 42001/Course Guide/topics]:
Annex B of ISO/IEC 42001 and control domain A.8 delineate that human oversight must be substantive and effective rather than superficial or performative. Simply inserting an " Approve " button into a user interface creates an illusion of human-in-the-loop control, especially when human reviewers succumb to automation bias due to lack of contextual input data, rationale transparency, and adequate review time. Under the standard's human agency and oversight principles, supervisory personnel must be equipped with intelligible operational context, actionable confidence scores, and accessible input telemetry to exercise genuine independent judgment, validate outputs, and execute overrides when necessary. Superficial approval workflows fail the governance criteria established by ISO/IEC 42001 for responsible algorithmic deployment.
Reference: ISO/IEC 42001:2023 Annex B.4 (Human oversight); Annex A.8 (AI system operations); GAICC Foundation Module 6 (Human-in-the-Loop & Oversight Architectures).

NEW QUESTION # 37
A foundation workshop case describes a small financial-advisory firm that has just signed its AI policy. The compliance officer asks what the firm should do next to translate the policy into operational practice for a new portfolio-recommendation AI tool the firm is preparing to deploy. Which next step BEST reflects how ISO
/IEC 42001 expects policy to connect to planning and operations for a specific AI system?

A. Conduct an AI risk assessment under Clause 6.1.2 and an AI System Impact Assessment under Clause
6.1.4 for the portfolio-recommendation tool, then plan risk treatment with controls aligned to the policy' s commitments.
B. Defer further action until the firm has accumulated several months of live experience with the portfolio- recommendation tool, on the basis that risk and impact assessments are more accurate when informed by post-deployment operational data points.
C. Re-sign the AI policy in front of staff at the next quarterly town-hall meeting to demonstrate leadership commitment, on the basis that visible re-signing reinforces the message conveyed by the original signature at policy adoption.
D. Print and laminate the signed policy for display in the office reception area, then distribute copies to each adviser ' s desk so that the document is visible during client meetings held in the firm ' s premises across the next quarter.

Answer: A

NEW QUESTION # 38
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