AIGP - IAPP Certified Artificial Intelligence Governance Professional–Efficient Reliable Exam Review

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IAPP AIGP Exam Syllabus Topics:

TopicDetails
Topic 1
  • Understanding the Foundations of AI Governance: This section of the exam measures skills of AI governance professionals and covers the core concepts of AI governance, including what AI is, why governance is needed, and the risks and unique characteristics associated with AI. It also addresses the establishment and communication of organizational expectations for AI governance, such as defining roles, fostering cross-functional collaboration, and delivering training on AI strategies. Additionally, it focuses on developing policies and procedures that ensure oversight and accountability throughout the AI lifecycle, including managing third-party risks and updating privacy and security practices.
Topic 2
  • Understanding How Laws, Standards, and Frameworks Apply to AI: This section of the exam measures skills of compliance officers and covers the application of existing and emerging legal requirements to AI systems. It explores how data privacy laws, intellectual property, non-discrimination, consumer protection, and product liability laws impact AI. The domain also examines the main elements of the EU AI Act, such as risk classification and requirements for different AI risk levels, as well as enforcement mechanisms. Furthermore, it addresses the key industry standards and frameworks, including OECD principles, NIST AI Risk Management Framework, and ISO AI standards, guiding organizations in trustworthy and compliant AI implementation.
Topic 3
  • Understanding How to Govern AI Development: This section of the exam measures the skills of AI project managers and covers the governance responsibilities involved in designing, building, training, testing, and maintaining AI models. It emphasizes defining the business context, performing impact assessments, applying relevant laws and best practices, and managing risks during model development. The domain also includes establishing data governance for training and testing, ensuring data quality and provenance, and documenting processes for compliance. Additionally, it focuses on preparing models for release, continuous monitoring, maintenance, incident management, and transparent disclosures to stakeholders.
Topic 4
  • Understanding How to Govern AI Deployment and Use: This section of the exam measures skills of technology deployment leads and covers the responsibilities associated with selecting, deploying, and using AI models in a responsible manner. It includes evaluating key factors and risks before deployment, understanding different model types and deployment options, and ensuring ongoing monitoring and maintenance. The domain applies to both proprietary and third-party AI models, emphasizing the importance of transparency, ethical considerations, and continuous oversight throughout the model’s operational life.

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IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q48-Q53):

NEW QUESTION # 48
What is most likely the first action that a developer takes to map, plan and scope an AI project?

Answer: A

Explanation:
The correct answer is A because the first step in any AI project lifecycle is to clearly define the business objective and justify the use of AI. AI governance frameworks emphasize that planning begins with understanding the purpose, value, and necessity of the system before moving into design or risk assessment stages. Establishing a business case ensures alignment with organizational goals, identifies expected benefits, and evaluates whether AI is the appropriate solution. This step corresponds to the planning phase of the AI lifecycle, where objectives and intended outcomes are documented. In contrast, TEVV processes occur during development and testing, while impact assessments and redress considerations arise later as part of risk management and governance. Starting with a clear "why AI" foundation ensures responsible, efficient, and goal-oriented system development.


NEW QUESTION # 49
Scenario:
A U.S.-based AI governance professional is evaluating resources from the National Institute of Standards and Technology (NIST) to guide the organization's AI risk assessment strategy. They are particularly interested in programs focused on assessing AI-specific impacts.
The main purpose of NIST'sAssessing Risks and Impacts of AI (ARIA)program is to:

Answer: A

Explanation:
The correct answer isA. TheARIA programby NIST is explicitly designed tosupport stakeholders in understanding and managing the risks and impactsof AI systems.
From the AIGP ILT Guide - U.S. Risk Frameworks Module:
"NIST's ARIA program develops and pilots assessment tools for AI risks and impacts, aimed at improving organizational capacity for responsible AI use." Also cited in the AI Governance in Practice Report2025(Frameworks Section):
"ARIA supports and aligns with the AI Risk Management Framework by helping organizations assess AI harms, safety concerns, and societal implications." ARIA isnota red-teaming or sandbox program-it's anassessment and governance resource.


NEW QUESTION # 50
Scenario:
A large multinational organization is rolling out a company-wide AI governance initiative. To build awareness and support adoption, they are evaluating different ways to train employees and stakeholders across departments, including legal, technical, marketing, and customer-facing roles.
Which of the following typical approaches is a large organization least likely to use to responsibly train stakeholders on AI terminology, strategy and governance?

Answer: D

Explanation:
The correct answer is A. While educating technical staff is important, expecting all technical employees to be retooled as AI developers is unrealistic and not aligned with scalable governance practices.
From the AIGP ILT Guide:
"Training approaches should be role-specific and align with the individual's function and responsibilities...
Organizations typically do not expect every technical role to participate in model development." The AI Governance in Practice Report 2024 supports tailored approaches:
"Cross-functional training should be specific to the individual's role and exposure to AI risk... Role-based education supports scalability and comprehension." Thus, broad development training for all technical employees is the least practical and least likely approach.


NEW QUESTION # 51
The White House Executive Order from November 2023 requires companies that develop dual- use foundation models to provide reports to the federal government about all of the following EXCEPT:

Answer: D

Explanation:
Under the White House Executive Order on Artificial Intelligence (EO 14110), companies developing dual-use foundation models are required to report specific information to the federal government. These requirements include:
1. Ongoing or planned activities related to training, developing, or producing dual-use foundation models, including physical and cybersecurity protections taken to assure the integrity of the training process against sophisticated threats.
2. Ownership and possession of the model weights of any dual-use foundation models, and the physical and cybersecurity measures taken to protect those model weights.
3. The results of any developed dual-use foundation model's performance in relevant AI red-team testing, including a description of any associated measures the company has taken to meet safety objectives, such as mitigations to improve performance on these red-team tests and strengthen overall model security.
4. Other information pertaining to the safety and reliability of dual-use foundation models, or activities or risks that present concerns to U.S. national security.
Notably, the EO does not mandate companies to conduct or report on environmental impact studies for each dual-use foundation model. Therefore, option C is not a required reporting obligation under the Executive Order.


NEW QUESTION # 52
A company plans on procuring a tool from an AI provider for its employees to use for certain business purposes. Which contractual provision would best protect the company's intellectual property in the tool, including training and testing data?

Answer: D

Explanation:
Indemnification provisions protect the company against intellectual property infringement claims arising from the provider's tool, including data used in training and testing.


NEW QUESTION # 53
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