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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
Exam Price:	USD 649 (members) / USD 799 (non-members)
Related Certifications:	CIPT CIPM CIPP
Passing Score:	300 (scaled score out of 500)
Certificate Validity Period:	2 years
Real Exam Qty:	100
Exam Format:	Multiple-choice, Scenario-based
Available Languages:	English
Exam Duration:	165 (including 15-minute optional break)
Recommended Training:	IAPP Training & Resources Official AIGP Body of Knowledge & Study Guide
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

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IAPP AIGP Exam Syllabus Topics:

Topic	Details
Topic 1	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 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 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 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 (Q15-Q20):

NEW QUESTION # 15
Decreasing the complexity of a machine learning model reduces variance and:

A. Increases accuracy.
B. Decreases tolerance.
C. Decreases interpretability.
D. Increases bias.

Answer: D

Explanation:
Reducing model complexity lowers variance but typically increases bias, reflecting a trade-off between underfitting and overfitting.

NEW QUESTION # 16
Which of the following may be permissible uses of an AI system under the EU AI Act EXCEPT?

A. Detecting emotions in a telemedicine session
B. Using biometrics in abduction cases
C. Improving the response time for emergency services
D. Detecting emotions in a workplace for employee morale

Answer: D

Explanation:
The correct answer is D. Emotion recognition in the workplace is flagged as unacceptable or highly restricted under the EU AI Act due to its intrusive nature and potential for misuse.
From the AIGP ILT Guide - EU AI Act Training Module:
"AI systems that monitor individuals' emotions in the workplace or educational settings are listed among prohibited or strictly limited practices under Article 5." AI Governance in Practice Report 2024 supports this interpretation:
"Emotion recognition systems, especially in sensitive contexts such as employment or education, raise significant concerns under EU fundamental rights law and are likely to be restricted." Other uses listed-such as emergency response or emotion detection in healthcare-may fall under lawful and beneficial uses, especially when justified by public interest.

NEW QUESTION # 17
CASE STUDY
Please use the following to answer the next question:
A local police department in the United States procured an AI system to monitor and analyze social media feeds, online marketplaces and other sources of public information to detect evidence of illegal activities (e.g., sale of drugs or stolen goods). The AI system works by surveying the public sites in order to identify individuals that are likely to have committed a crime.
It cross-references the individuals against data maintained by law enforcement and then assigns a percentage score of the likelihood of criminal activity based on certain factors like previous criminal history, location, time, race and gender.
The police department retained a third-party consultant to assist in the procurement process, specifically to evaluate two finalists. Each of the vendors provided information about their system's accuracy rates, the diversity of their training data and how their system works. The consultant determined that the first vendor's system has a higher accuracy rate and based on this information, recommended this vendor to the police department.
The police department chose the first vendor and implemented its AI system. As part of the implementation, the department and consultant created a usage policy for the system, which includes training police officers on how the system works and how to incorporate it into their investigation process.
The police department has now been using the AI system for a year. An internal review has found that every time the system scored a likelihood of criminal activity at or above 90%, the police investigation subsequently confirmed that the individual had, in fact, committed a crime. Based on these results, the police department wants to forego investigations for cases where the AI system gives a score of at least 90% and proceed directly with an arrest.
What is the best reason the police department should continue to perform investigations even if the AI system scores an individual's likelihood of criminal activity at or above 90%?

A. Because the department did not perform an impact assessment for this intended use.
B. Because AI systems that affect fundamental civil rights should not be fully automated.
C. Because investigations may uncover information relevant to sentencing.
D. Because investigations may identify additional individuals involved in the crime.

Answer: B

Explanation:
AI systems impacting fundamental civil rights, such as arrests, require human oversight to prevent unfair automated decisions and ensure due process.

NEW QUESTION # 18
Scenario:
An organization is developing a powerful general-purpose AI (GPAI) model that has systemic impact. The compliance team is assessing what legal obligations apply under the EU AI Act.
Under the EU AI Act, which of the following compliance actions appliesonly to General Purpose AI models with systemic risk?

A. Making information available to downstream providers who integrate the model into their AI systems
B. Publishing a detailed summary of the data used to train the model
C. Implementing an intellectual property policy to comply with EU copyright laws
D. Maintaining up-to-date technical documentation, including testing details

Answer: B

Explanation:
The correct answer isA. Only GPAI modelswith systemic riskmustpublish a detailed summary of training datato meet transparency and accountability standards under the EU AI Act.
From the AI Governance in Practice Report2025(EU AI Act Section):
"For GPAI systems with systemic risk, providers must publish sufficiently detailed summaries of the content used to train the model." Also, the AIGP ILT Guide confirms:
"The obligation to disclose summaries of training data applies only to systemic-risk GPAI models, not all general-purpose models or high-risk systems." This unique requirement is part of the Act's effort to increasetransparency and auditabilityfor powerful foundational models.

NEW QUESTION # 19
ISO/IEC 22989 and 42001 can be valuable resources for AI Governance professionals in all of the following ways EXCEPT:

A. Establishing terminology and describing concepts so that governance team members can communicate with diverse parties and stakeholders from around the world.
B. Addressing specific issues related to managing procurement processes with third parties that provide or develop AI systems for their organization.
C. Recommending key activities to assess and manage risk: test, evaluate, verify and validate (TEVV).
D. Being applicable to organizations of any size and industry seeking to use AI responsibly and effectively in their design processes, information systems and controls.

Answer: B

Explanation:
ISO/IEC 22989 and 42001 provide foundational concepts, terminology, and governance guidance for AI systems, but they do not address the detailed, specific processes required for managing procurement with third-party AI providers.

NEW QUESTION # 20
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