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IAPP AIGP Exam Overview:

Certification Vendor:	IAPP
Exam Name:	IAPP Certified Artificial Intelligence Governance Professional
Exam Number:	AIGP
Related Certifications:	CIPT CIPP/US CIPP/A CIPM CIPP/E
Exam Price:	USD 550
Passing Score:	300
Exam Format:	Multiple-choice
Exam Duration:	150 minutes
Certificate Validity Period:	2 Years
Available Languages:	English
Real Exam Qty:	100
Sample Questions:	IAPP AIGP Sample Questions
Exam Way:	Online (OnVUE) or Test Center (Pearson VUE)
Pre Condition:	No specific prerequisites. Recommended background in privacy, compliance, legal, or technology.
Official Syllabus URL:	https://iapp.org/certify/aigp/

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IAPP AIGP Exam Syllabus Topics:

Topic	Details
Topic 1	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 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 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 4	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.

IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q96-Q101):

NEW QUESTION # 96
CASE STUDY
Please use the following to answer the next question:
A leading insurance provider that offers a range of coverage options to individuals has decided to utilize AI to streamline and improve its customer acquisition and underwriting process, including the accuracy and efficiency of pricing policies. The company has engaged a cloud provider to utilize and fine-tune its pre-trained, general purpose large language model ("LLM").
The company intends to use its historical customer data - including applications, policies and claims - and proprietary pricing and risk strategies to provide an initial qualification assessment of potential customers, which would then be routed to a human underwriter for final review.
The company and the cloud provider have completed training and testing the LLM, performed a readiness assessment, and made the decision to deploy the LLM into production. They have designated an internal compliance team to monitor the model during the first month, specifically to evaluate the accuracy, fairness and reliability of its output.
After the first month in production, the company realizes that the LLM declines a higher percentage of women's applications.
Each of the following steps would support fairness testing by the compliance team during the first month in production EXCEPT:

A. Using tools to help understand factors that may account for differences in decision-making.
B. Validating a similar level of decision-making across different demographic groups.
C. Providing the applicants with information about the model capabilities and limitations.
D. Identifying if additional training data should be collected for specific demographic groups.

Answer: C

Explanation:
Providing applicants with information about model capabilities is important for transparency but does not directly support fairness testing, which focuses on evaluating and mitigating bias in decision-making.

NEW QUESTION # 97
A company launched an AI model last year. One year later, the company was acquired and the entire team that developed, deployed and oversaw the model left. How can the company best maintain the model from a governance perspective going forward?

A. Hire key employees subject to non-compete clauses.
B. Create a library of all documentation created during the AI lifecycle.
C. Create a trust center on the company's website with its ethical principles.
D. Form an oversight committee responsible for all model decisions.

Answer: B

Explanation:
Maintaining comprehensive documentation of the AI lifecycle is essential for governance continuity, enabling new teams to understand, manage, and update the model responsibly.

NEW QUESTION # 98
Which of the following use cases would be best served by a non-AI solution?

A. An e-commerce provider wants to make personalized recommendations.
B. A non-profit wants to develop a social media presence.
C. A customer service agency wants to automate answers to common questions.
D. A business analyst wants to develop advertising campaigns.

Answer: B

Explanation:
The correct answer is A because developing a social media presence typically does not require AI and can be effectively achieved through traditional digital marketing strategies, content planning, and manual engagement. AI governance principles emphasize that organizations should first determine whether AI is necessary or proportionate to the problem being solved. Using AI where simpler, deterministic, or human-driven solutions suffice can introduce unnecessary complexity, cost, and risk. In contrast, options B, C, and D involve tasks such as campaign optimization, personalization, and automation, which benefit significantly from AI capabilities like pattern recognition, predictive analytics, and natural language processing. Responsible AI governance encourages a "fit-for-purpose" approach, ensuring AI is only deployed when it provides clear added value over non-AI alternatives.

NEW QUESTION # 99
A shipping service based in the US is looking to expand its operations into the EU. It utilizes an in-house developed multimodal AI model that analyzes all personal data collected from shipping senders and recipients, and optimizes shipping routes and schedules based on this data.
As they expand into the EU, all of the following descriptions should be included in the technical documentation for their AI model EXCEPT?

A. A detailed description of the elements of the AI system and of the process for its development.
B. A general description of the AI system.
C. A description of the prioritization of the risks of deployment of the AI system.
D. A description of the appropriateness of the performance metrics for the specific AI system.

Answer: C

Explanation:
The EU AI Act outlines what must be included intechnical documentationfor high-risk systems. These requirements are designed to supportconformity assessment, transparency, and traceability.
From theAI Governance in Practice Report 2024:
"It mandates drawing up technical documentation... must include a general description of the AI system, the intended purpose, and a detailed description of the elements and development process." (p. 34)
"Documentation... includes training, testing, evaluation procedures, andappropriateness of performance metrics." (p. 34-35) Therisk management systemis addressed separately through arisk management plan, not within the technical documentation itself.
Thus:
* A, C, and Dare explicitly required in thetechnical documentation.
* B, while important, is part of therisk management process, not a required section oftechnical documentation.

NEW QUESTION # 100
CASE STUDY
Please use the following to answer the next question:
You have recently assumed the role of AI Governance leader for a California-based medical technology company. The organization primarily serves hospitals and has recently expanded to include walk-in clinics located within local pharmacies.
The company ' s core business focuses on diagnostic assistance powered by a large language model LLM and back-office process optimization using Agentic AI, including chatbots, medical record request handling, scheduling and billing.
In preparation for its next round of funding, the board has asked you to prepare an AI Risk report to demonstrate to investors how the company is addressing AI-related risks. In preparing the report you learn that last year the company generated 30 million dollars in gross revenue across the US, EU, India, and South Korea and that vendors are engaged for various activities, including model testing and providing third-party AI solutions for chatbots.
Which of the following responses is least likely to meet mandatory transparency requirements in any of the applicable laws?

A. A model card provided to healthcare providers.
B. A link to the company ' s AI policy and AI code of conduct clearly placed on the company ' s website.
C. A label at the bottom of patient summaries that indicates an AI tool assisted in generating the summary.
D. A pop-up message that alerts patients when they are interacting with a chatbot.

Answer: B

Explanation:
The correct answer is C because simply publishing a general AI policy or code of conduct does not satisfy specific transparency obligations required by AI regulations. Transparency requirements focus on providing clear, context-specific disclosures to affected individuals about how AI is being used, particularly when it directly impacts them. For example, notifying users when they are interacting with an AI system or labeling AI-generated content are explicit transparency measures aligned with regulatory expectations. The AI Governance in Practice Report highlights that transparency includes informing users when they interact with AI systems and providing meaningful information about outputs and system behavior . Model cards and labels support system-level and output-level transparency, while real-time notices ensure user awareness. In contrast, a general policy link lacks immediacy, specificity, and user relevance, making it insufficient for mandatory transparency compliance.

NEW QUESTION # 101
......

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