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IAPP AIGP Testking Braindumps - in .pdf Free Demo

  • Exam Code: AIGP
  • Exam Name: IAPP Certified Artificial Intelligence Governance Professional
  • Last Updated: Nov 05, 2026
  • Q & A: 219 Questions and Answers
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  • Exam Code: AIGP
  • Exam Name: IAPP Certified Artificial Intelligence Governance Professional
  • Last Updated: Nov 05, 2026
  • Q & A: 219 Questions and Answers
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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 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 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.

Reference: https://iapp.org/certify/aigp/

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IAPP Certified Artificial Intelligence Governance Professional Sample Questions:

Question #1

Your organization is searching for a new way to help accurately forecast sales predictions by various types of customers.
Which of the following is the best type of model to choose if your organization wants to customize the model and avoid lock-in?

  • A. A free large language model.
  • B. A proprietary generative AI model.
  • C. A classic machine learning model.
  • D. A subscription-based, multimodal model.
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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Question #2

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

  • A. A business analyst wants to forecast future cost overruns and underruns.
  • B. A non-profit wants to develop a social media presence.OB. An e-commerce provider wants to make personalized recommendations.
  • C. A customer service agency wants automate answers to common questions.
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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Question #3

All of the following are required for high-risk AI systems under the EU AI Act EXCEPT?

  • A. Retaining system-generated logs for at least six months.
  • B. Publishing a detailed report on the training data used.
  • C. Conducting a conformity assessment.
  • D. Conducting post-market monitoring.
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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Question #4

CASE STUDY
Please use the following answer the next question:
ABC Corp, is a leading insurance provider offering a range of coverage options to individuals. ABC has decided to utilize artificial intelligence to streamline and improve its customer acquisition and underwriting process, including the accuracy and efficiency of pricing policies.
ABC has engaged a cloud provider to utilize and fine-tune its pre-trained, general purpose large language model ("LLM"). In particular, ABC 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 a human underwriter for final review.
ABC 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. ABC has 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, ABC realizes that the LLM declines a higher percentage of women's loan applications due primarily to women historically receiving lower salaries than men.
Which of the following is the most important reason to train the underwriters on the model prior to deployment?

  • A. To apply their own judgment to the initial assessment.
  • B. To solicit on-going feedback on model performance.
  • C. To provide a reminder of a right appeal.
  • D. To ensure they provide transparency applicants on the model.
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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Question #5

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?

  • A. The consulting firm.
  • B. The cloud provider.
  • C. The healthcare network'sdata science team.
  • D. The healthcare network's Al governance committee.
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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