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IAPP AIGP Exam Overview:

Certification Vendor:IAPP (International Association of Privacy Professionals)
Exam Name:IAPP Certified Artificial Intelligence Governance Professional Exam
Exam Number:AIGP
Certificate Validity Period:2 years
Real Exam Qty:100
Available Languages:English
Related Certifications:CIPM
CIPP
CIPT
Passing Score:300 (scaled score out of 500)
Exam Price:USD 649 (members) / USD 799 (non-members)
Exam Duration:165 (including 15-minute optional break)
Exam Format:Multiple-choice, Scenario-based
Recommended Training:Official AIGP Body of Knowledge & Study Guide
IAPP Training & Resources
Exam Registration:Pearson VUE Scheduling
IAPP Official Registration
Sample Questions:IAPP AIGP Sample Questions
Exam Way:Online remote proctored or in-person at Pearson VUE test centers
Pre Condition:No formal prerequisites; open to all professionals
Official Syllabus URL:https://iapp.org/certify/aigp

>> Actual AIGP Test Answers <<

2026 Unparalleled IAPP AIGP: Actual IAPP Certified Artificial Intelligence Governance Professional Test Answers

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IAPP AIGP Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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.
Topic 3
  • 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 4
  • 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.

IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q143-Q148):

NEW QUESTION # 143
You asked a generative AI tool to recommend new restaurants to explore in Boston, Massachusetts that have a specialty Italian dish made in a traditional fashion without spinach and wine. The generative AI tool recommended five restaurants for you to visit.
After looking up the restaurants, you discovered one restaurant did not exist and two others did not have the dish.
This information provided by the generative AI tool is an example of what is commonly called:

Answer: C

Explanation:
The AI generating incorrect or fabricated information, like nonexistent restaurants, is referred to as hallucination.


NEW QUESTION # 144
A company subject to GDPR is building its governance framework for how it will collect data to be used for training of AI models. The most important thing the company can do to ensure GDPR compliance is:

Answer: B

Explanation:
Minimizing the amount of personal data used in training supports GDPR's data minimization principle, reducing privacy risks and improving compliance.


NEW QUESTION # 145
CASE STUDY
A global marketing agency is adapting a large language model ("LLM") to generate content for an upcoming marketing campaign for a client's new product: a hard hat designed for construction workers of any gender to better protect them from head injuries.
The marketing agency is accessing the LLM through an application programming interface ("API") developed by a third-party technology company. They want to generate text to be used for targeted advertising communications that highlight the benefits of the hard hat to potential purchasers. Both the marketing agency and the technology company have taken reasonable steps to address Al governance.
The marketing company has:
* Entered into a contract with the technology company with suitable representations and warranties.
* Completed an impact assessment on the LLM for this intended use.
* Built technical guidance on how to measure and mitigate bias in the LLM.
* Enabled technical aspects of transparency, explainability, robustness and privacy.
* Followed applicable regulatory requirements.
* Created specific legal statements and disclosures regarding the use of the Al on its client's advertising.
The technology company has:
* Provided guidance and resources to developers to address environmental concerns.
* Build technical guidance on how to measure and mitigate bias in the LLM.
* Provided tools and resources to measure bias specific to the LLM.
* Enabled technical aspects of transparency, explainability, robustness and privacy.
* Mapped and mitigated potential societal harms and large-scale impacts.
* Followed applicable regulatory requirements and industry standards.
* Created specific legal statements and disclosures regarding the LLM. including with respect to IP and rights to data.
Which stakeholder is responsible for the lawful collection of data used to train the foundational AI model?

Answer: D

Explanation:
The correct answer is B - The tech company. The party that develops and trains the foundational model is responsible for ensuring the lawful collection of training data.
From the AIGP ILT Guide - Foundational Models & Data Governance:
"Responsibility for the lawfulness of data collection typically lies with the party that trains the model- usually the provider or developer of the foundational model." AI Governance in Practice Report 2024 confirms:
"General Purpose AI providers are required to ensure that training data is lawfully acquired, including compliance with intellectual property and privacy requirements." The marketing agency is only a user or downstream integrator, not responsible for original data collection.


NEW QUESTION # 146
Which of the following is a subcategory of AI and machine learning that uses labeled datasets to train algorithms?

Answer: C

Explanation:
Supervised learning uses labeled datasets to train algorithms by providing input-output pairs for learning.


NEW QUESTION # 147
A company that deploys AI but is not currently a provider or developer intends to develop and market its own AI system. Which obligation would then be likely to apply?

Answer: B

Explanation:
Once the company becomes a provider of an AI system, it becomes subject to the EU AI Act's provider obligations, the foundational one being the requirement to implement a formal risk- management framework for the system throughout its lifecycle.


NEW QUESTION # 148
......

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