IAPP AIGP Authentic Exam Questions - AIGP New Real Test

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IAPP AIGP Exam Overview:

Certification Vendor:	IAPP (International Association of Privacy Professionals)
Exam Name:	IAPP Certified Artificial Intelligence Governance Professional (AIGP) Exam
Exam Number:	AIGP
Certificate Validity Period:	2 years
Related Certifications:	CIPT CIPP/US CIPM CIPP/E
Exam Duration:	165 minutes
Passing Score:	300 (scaled score out of 100–500)
Exam Format:	Single-select, Scenario-based questions, Multi-select, Multiple-choice
Real Exam Qty:	100 (85 scored + ~15 unscored pilot questions)
Exam Price:	USD 799 (non-member) / USD 649 (IAPP member)
Available Languages:	English
Recommended Training:	IAPP Official AIGP Training and Resources AIGP Practice Exam (Official IAPP Store)
Exam Registration:	Pearson VUE Scheduling Portal (via IAPP account) Official IAPP AIGP Exam Registration
Sample Questions:	IAPP AIGP Sample Questions
Exam Way:	Computer-based exam delivered via Pearson VUE (test center or online proctored OnVUE)
Pre Condition:	None
Official Syllabus URL:	https://iapp.org/certify/aigp

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IAPP AIGP Exam Syllabus Topics:

Topic	Details
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 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 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 (Q168-Q173):

NEW QUESTION # 168
CASE STUDY
Please use the following to answer the next question:
A mid-size US healthcare network has decided to develop an AI solution to detect a type of cancer that is most likely to 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 to a radiologist for secondary review pursuant to agreed-upon criteria (e.g., a confidence score below a threshold).
To date, the healthcare network has:
- Defined its AI ethical principles.
- Conducted discovery to identify the intended uses and success
criteria for the system.
- Established an AI risk committee.
- Assembled a cross-functional team with clear roles and
responsibilities.
- 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. It also intends to retain a large consulting firm to supplement its small data science team and 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 of the following steps can best mitigate the possibility of discrimination prior to training and testing the AI solution?

A. Engage a third party to perform an audit.
B. Create a bias bounty program.
C. Perform an impact assessment.
D. Procure more data from clinical research partners.

Answer: C

Explanation:
Performing an impact assessment prior to training and testing helps identify potential discrimination risks early, enabling mitigation strategies before deployment.

NEW QUESTION # 169
The best practice to manage third-party risk associated with AI systems is to create and implement policies that:

A. Focus on the financial stability of third-party vendors as the primary criterion for risk assessment.
B. Provide for an appropriate level of due diligence and ongoing monitoring based on the defined risk.
C. Focus on the technical aspects of AI systems, such as data security, while ethical risks are addressed through suitable contracts.
D. Require third-party AI systems to undergo a comprehensive audit by an external cybersecurity firm every six months.

Answer: B

Explanation:
Effective third-party AI risk management requires policies that establish a risk-based approach with appropriate due diligence and ongoing monitoring proportional to the level of risk posed by the third-party system.

NEW QUESTION # 170
To maintain fairness in a deployed system, it is most important to?

A. Detect anomalies outside established metrics that require new training data.
B. Monitor for data drift that may affect performance and accuracy.
C. Protect against loss of personal data in the model.
D. Optimize computational resources and data to ensure efficiency and scalability.

Answer: B

Explanation:
To maintain fairness in a deployed system, it is crucial to monitor for data drift that may affect performance and accuracy. Data drift occurs when the statistical properties of the input data change over time, which can lead to a decline in model performance. Continuous monitoring and updating of the model with new data ensure that it remains fair and accurate, adapting to any changes in the data distribution. Reference: AIGP Body of Knowledge on Post-Deployment Monitoring and Model Maintenance.

NEW QUESTION # 171
CASE STUDY
A company is considering the procurement of an AI system designed to enhance the security of IT infrastructure. The AI system analyzes how users type on their laptops, including typing speed, rhythm and pressure, to create a unique user profile. This data is then used to authenticate users and ensure that only authorized personnel can access sensitive resources.
When prioritizing the updates to its policies, rules and procedures to include the new AI system for user authentication, the organization should:

A. Reduce the complexity of the policy to make it easier for non-technical employees to understand
B. Update security controls for sensitive data
C. Update third-party data sharing policies
D. Ensure that any personal data used is only processed for a specific and lawful purpose

Answer: D

Explanation:
The correct answeris.CThis action ties directly into principlesof dataminimization, purpose limitation,and lawfulnessof processing, which are central to privacy and AI governance.
From the AIGP Body of Knowledge, Section on Privacy Considerations:
"Personal data must only be processed for specified and lawful purposes. Organizations must consider whether they have a legal basis for processing such data under data protection laws like the GDPR or CCPA." Additionally, AI Governance in Practice Report2025emphasizes:
"One of the most significant challenges when designing and developing AI systems is ensuring the data used is appropriate for the intended purpose... Managing unnecessary data, especially data that may contain sensitive attributes, can increase risk."

NEW QUESTION # 172
Which of the following would be the least likely step for an organization to take when designing an integrated compliance strategy for responsible Al?

A. Launching a survey to understand the concerns and interests of potentially impacted stakeholders.
B. Conducting an assessment of existing compliance programs to determine overlaps and integration points.
C. Consulting experts to consider the ethical principles underpinning the use of Al within the organization.
D. Employing a new software platform to modernize existing compliance processes across the organization.

Answer: D

Explanation:
When designing an integrated compliance strategy for responsible AI, the least likely step would be employing a new software platform to modernize existing compliance processes. While modernizing compliance processes is beneficial, it is not as directly related to the strategic integration of ethical principles and stakeholder concerns. More critical steps include conducting assessments of existing compliance programs to identify overlaps and integration points, consulting experts on ethical principles, and launching surveys to understand stakeholder concerns. These steps ensure that the compliance strategy is comprehensive and aligned with responsible AI principles. Reference: AIGP Body of Knowledge on AI Governance and Compliance Integration.

NEW QUESTION # 173
......

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