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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
Exam Price:	USD 799 (non-member) / USD 649 (IAPP member)
Real Exam Qty:	100 (85 scored + ~15 unscored pilot questions)
Passing Score:	300 (scaled score out of 100–500)
Exam Duration:	165 minutes
Certificate Validity Period:	2 years
Related Certifications:	CIPM CIPP/US CIPT CIPP/E
Available Languages:	English
Exam Format:	Scenario-based questions, Multi-select, Multiple-choice, Single-select
Recommended Training:	IAPP Official AIGP Training and Resources AIGP Practice Exam (Official IAPP Store)
Exam Registration:	Official IAPP AIGP Exam Registration Pearson VUE Scheduling Portal (via IAPP account)
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 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 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.

IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q75-Q80):

NEW QUESTION # 75
Which stakeholder is responsible for lawful collection of data for the training of the foundational AI model?

A. The marketing agency.
B. The data aggregator.
C. The marketing agency ' s client.
D. The tech company.

Answer: B

Explanation:
Data aggregators are third parties that collect and license data from various sources. They are responsible for ensuring thelawful collectionandproper usage rightsof the data they distribute - especially when such data is used to train foundational AI models.
From theAI Governance in Practice Report 2025:
"As organizations have neither proximity to how third-party data was first collected nor direct control over the data governance practices of third parties, an organization can benefit from carrying out its own legal due diligence and third-party risk management." (p. 19)
"Legal due diligence may include verification of the personal data ' s lawful collection by the databroker..." (p. 19) This confirms thatdata aggregatorsbear the legal and ethical burden to verify that data has been lawfully collected and is appropriately licensed for use, including in AI training.
* A. The marketing agencyandD. its clientmay use data, but they rely on upstream providers for its lawful origin.
* B. The tech companymay train the model but depends on lawful sourcing by data aggregators.

NEW QUESTION # 76
All of the following are included within the scope of post-deployment AI maintenance EXCEPT:

A. Defining thresholds to conduct new impact assessments.
B. Dedicating experts to continually monitor the model output.
C. Ensuring that all model components are subject to a control framework.
D. Evaluating the need for an audit under certain standards.

Answer: C

Explanation:
Ensuring all model components are subject to a control framework is typically addressed during development and governance setup, not specifically post-deployment maintenance.

NEW QUESTION # 77
What is the 1956 Dartmouth summer research project on AI best known as?

A. A research project to create a test for machine intelligence.
B. A research project on the impacts of technology on society.
C. A meeting focused on the impacts of the launch of the first mass-produced computer.
D. A meeting focused on the founding of the AI field.

Answer: D

Explanation:
The 1956 Dartmouth summer research project is best known as the event that formally founded the field of artificial intelligence.

NEW QUESTION # 78
CASE STUDY
A premier payroll services company that employs thousands of people globally, is embarking on a new hiring campaign and wants to implement policies and procedures to identify and retain the best talent. The new talent will help the company's product team expand its payroll offerings to companies in the healthcare and transportation sectors, including in Asia.
It has become time consuming and expensive for HR to review all resumes, and they are concerned that human reviewers might be susceptible to bias.
To address these concerns, the company is considering using a third-party Al tool to screen resumes and assist with hiring. They have been talking to several vendors about possibly obtaining a third-party Al-enabled hiring solution, as long as it would achieve its goals and comply with all applicable laws.
The organization has a large procurement team that is responsible for the contracting of technology solutions. One of the procurement team's goals is to reduce costs, and it often prefers lower-cost solutions. Others within the company deploy technology solutions into the organization's operations in a responsible, cost-effective manner.
The organization is aware of the risks presented by Al hiring tools and wants to mitigate them. It also questions how best to organize and train its existing personnel to use the Al hiring tool responsibly. Their concerns are heightened by the fact that relevant laws vary across jurisdictions and continue to change.
All of the following are potential negative consequences created by using the AI tool to help make hiring decisions EXCEPT?

A. Disparate impacts
B. Automation bias
C. Privacy violations
D. Candidate quality

Answer: D

Explanation:
The correct answer isB. "Candidate quality" isnota negative consequence of using AI-rather, it is the intendedbenefitof using such tools (e.g., more efficient filtering of strong candidates).
From the AIGP ILT Guide:
"Automation bias, disparate impact, and privacy risks are well-documented concerns in AI-assisted hiring. These risks may arise when AI models replicate biases present in training data or obscure the decision logic." AI Governance in Practice Report 2025 (Bias and Fairness Section) also warns:
"Improper AI use in hiring can lead to disparate impact, where neutral criteria disproportionately disadvantage protected groups." Candidate quality is agoal, not a risk, makingB the correct answerfor what isnota negative outcome.

NEW QUESTION # 79
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.
The data processed by the AI system would be classified as:

A. Special category data, if it can be used to uniquely identify a person
B. Organizational data, since it is part of the authentication process
C. Non-sensitive personal data, since it does not reveal information about health, gender or race
D. Non-personal data, as long as it is not linked to a user ID

Answer: A

Explanation:
The correct answer isD.Keystroke dynamics, used to identify individuals, fallunder biometricdata, which isa specialcategory of personaldata underthe GDPR and other frameworks.
From the AI Governance in Practice Report2025:
"Keystroke dynamics may constitute biometric data if used to uniquely identify an individual... Biometric data is classified as special category personal data and requires higher protection standards." Also reflected in ILT Participant Guide:
"Biometric data, such as facial images, voiceprints, iris scans or keystroke patterns, are treated as special category data when they are used for the purpose of uniquely identifying individuals."

NEW QUESTION # 80
......

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