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IAPP AIGP Exam Syllabus Topics:

SectionObjectives
Foundations of AI Governance- AI Governance Fundamentals
  • 1. Key AI Terminology and Concepts
  • 2. Understanding the AI Development Life Cycle
  • 3. Defining AI and its different approaches
- Impacts of AI
  • 1. Risks of AI
  • 2. Benefits of AI
AI Governance Management- Life Cycle Management
  • 1. Incident Management
  • 2. Auditing and Monitoring
  • 3. Third-party management
- Emerging Issues
  • 1. Generative AI
  • 2. Future Trends
  • 3. Ethical AI
AI Risk Management- Risk Frameworks and Standards
  • 1. NIST AI Risk Management Framework (RMF)
  • 2. ISO 31000 Risk Management
- Operationalizing Risk Management
  • 1. Risk mitigation strategies
  • 2. Risk identification and assessment
AI Governance Implementation- Data Governance for AI
  • 1. Data Quality and Integrity
  • 2. Data Privacy and Protection
- Organizational Governance
  • 1. Roles and Responsibilities (RACI)
  • 2. Governance Structures
  • 3. Policies and Procedures
AI Laws, Regulations, and Standards- Global AI Frameworks
  • 1. OECD AI Principles
  • 2. ISO/IEC Standards
  • 3. UNESCO AI Ethics
- Regional and National Regulations
  • 1. EU AI Act
  • 2. National AI Strategies
  • 3. US State and Federal Regulations

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IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q198-Q203):

NEW QUESTION # 198
A bank is aiming to comply with ISO/IEC 42005:2025, and is studying how to adopt the standard in light of a new AI customer service system that it would like to implement.
In addition to the risk management process the bank already has in place to assess the risks of any potential new systems, which of the following actions is the most effective in adopting the ISO/IEC 42005:2025 standard?

Answer: B

Explanation:
The correct answer is B because ISO/IEC 42005 emphasizes integrating AI risk management into existing enterprise risk management frameworks rather than creating siloed or duplicative processes. Effective AI governance requires embedding AI-specific risks into established governance structures such as risk registers, controls, and monitoring systems. This ensures consistency, scalability, and alignment with organizational risk practices. Options C and D introduce parallel or fragmented processes, which contradict the principle of integrated governance and may create inefficiencies or gaps. Option A focuses only on data collection and does not address governance integration. The AI Governance in Practice Report highlights that organizations should incorporate AI risks into broader enterprise risk management and maintain unified risk registers to ensure visibility, accountability, and coordinated mitigation across the organization.


NEW QUESTION # 199
CASE STUDY
Please use the following answer the next question:
A mid-size US healthcare network has decided to develop an Al solution to detect a type of cancer that is most likely arise in adults. Specifically, the healthcare network intends to create a recognition algorithm that will perform an initial review of all imaging and then route records a radiologist for secondary review pursuant agreed-upon criteria (e.g., a confidence score below a threshold).
To date, the healthcare network has taken the following steps: defined its Al ethical principles: conducted discovery to identify the intended uses and success criteria for the system: established an Al governance committee; assembled a broad, crossfunctional team with clear roles and responsibilities; and created policies and procedures to document standards, workflows, timelines and risk thresholds during the project.
The healthcare network intends to retain a cloud provider to host the solution and a consulting firm to help develop the algorithm using the healthcare network's existing data and de-identified data that is licensed from a large US clinical research partner.
Which stakeholder group is most important in selecting the specific type of algorithm?

Answer: D

Explanation:
In selecting the specific type of algorithm for the AI solution, the healthcare network's data science team is most important. This team possesses the technical expertise and understanding of the data, the clinical context, and the performance requirements needed to make an informed decision about which algorithm is most suitable. While the cloud provider and consulting firm can offer support and infrastructure, and the AI governance committee provides oversight, the data science team's specialized knowledge is crucial for selecting and implementing the appropriate algorithm. Reference: AIGP Body of Knowledge, AI governance and team roles section.


NEW QUESTION # 200
Scenario:
An organization is developing a powerful general-purpose AI (GPAI) model that has systemic impact. The compliance team is assessing what legal obligations apply under the EU AI Act.
Under the EU AI Act, which of the following compliance actions appliesonly to General Purpose AI models with systemic risk?

Answer: B

Explanation:
The correct answer isA. Only GPAI modelswith systemic riskmustpublish a detailed summary of training datato meet transparency and accountability standards under the EU AI Act.
From the AI Governance in Practice Report2025(EU AI Act Section):
"For GPAI systems with systemic risk, providers must publish sufficiently detailed summaries of the content used to train the model." Also, the AIGP ILT Guide confirms:
"The obligation to disclose summaries of training data applies only to systemic-risk GPAI models, not all general-purpose models or high-risk systems." This unique requirement is part of the Act's effort to increasetransparency and auditabilityfor powerful foundational models.


NEW QUESTION # 201
An AI system that maintains its level of performance within defined acceptable limits despite real world or adversarial conditions would be described as:

Answer: B

Explanation:
Robustness describes an AI system's ability to maintain performance despite variations or adversarial conditions in the environment.


NEW QUESTION # 202
CASE STUDY
Please use the following answer the next question:
A local police department in the United States procured an Al system to monitor and analyze social media feeds, online marketplaces and other sources of public information to detect evidence of illegal activities (e.g., sale of drugs or stolen goods). The Al system works by surveilling the public sites in order to identify individuals that are likely to have committed a crime. It cross-references the individuals against data maintained by law enforcement and then assigns a percentage score of the likelihood of criminal activity based on certain factors like previous criminal history, location, time, race and gender.
The police department retained a third-party consultant assist in the procurement process, specifically to evaluate two finalists. Each of the vendors provided information about their system's accuracy rates, the diversity of their training data and how their system works. The consultant determined that the first vendor's system has a higher accuracy rate and based on this information, recommended this vendor to the police department.
The police department chose the first vendor and implemented its Al system. As part of the implementation, the department and consultant created a usage policy for the system, which includes training police officers on how the system works and how to incorporate it into their investigation process.
The police department has now been using the Al system for a year. An internal review has found that every time the system scored a likelihood of criminal activity at or above 90%, the police investigation subsequently confirmed that the individual had, in fact, committed a crime. Based on these results, the police department wants to forego investigations for cases where the Al system gives a score of at least 90% and proceed directly with an arrest.
The best human oversight mechanism for the police department to implement is that a police officer should?

Answer: A

Explanation:
The best human oversight mechanism for the police department to implement is for a police officer to consider the AI recommendation as part of the criminal investigation. This ensures that the AI system's output is used as a tool to aid human decision-making rather than replace it. The police officer should integrate the AI's insights with other evidence and contextual information to make informed decisions, maintaining a balance between technological aid and human judgment. Reference: AIGP Body of Knowledge on AI Integration and Human Oversight.


NEW QUESTION # 203
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