Free AIGP: Artificial Intelligence Governance Professional Exam Questions and Answers
Artificial Intelligence Governance Professional is one of the IAPP tests covered here. The five IAPP credentials cover genuinely different ground — CIPP/E is European privacy law, CIPP/US American, CIPM programme management, CIPT privacy engineering and AIGP artificial-intelligence governance — and none is a prerequisite for another. What they share is the machinery: Pearson VUE delivery at a centre or online, scoring on a 100-to-500 scale with 300 to pass and the raw cut score deliberately withheld, and a two-year term kept alive with 20 continuing-education credits and a maintenance fee. The four core papers are 90 questions over two and a half hours; AIGP is 100.
Looking for AIGP exam dumps or ExamTopics AIGP questions? These AIGP practice questions cover the same ground with verified answers and explanations, a downloadable AIGP PDF and a full AIGP practice test, kept current as IAPP updates the exam.
Last updated: October 12, 2026
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Question #1
Please use the following answer the next question: Good Values Corporation (GVC) is a U.S. educational services provider that employs teachers to create and deliver enrichment courses for high school students. GVC has learned that many of its teacher employees are using generative AI to create the enrichment courses, and that many of the students are using generative AI to complete their assignments. In particular, GVC has learned that the teachers they employ used open source large language models (“LLM”) to develop an online tool that customizes study questions for individual students. GVC has also discovered that an art teacher has expressly incorporated the use of generative AI into the curriculum to enable students to use prompts to create digital art. GVC has started to investigate these practices and develop a process to monitor any use of generative AI, including by teachers and students, going forward. All of the following may be copyright risks from teachers using generative AI to create course content EXCEPT?
Correct answer: B
Explanation
All of the options listed may pose copyright risks when teachers use generative AI to create course content, except for students must expressly consent to this use of generative AI. While obtaining student consent is essential for ethical and privacy reasons, it does not directly relate to copyright risks associated with the creation and use of AI-generated content. Reference: The AIGP Body of Knowledge discusses the importance of addressing intellectual property (IP) risks when using AI-generated content. Copyright risks are typically associated with the use of third-party data and the lack of attribution, rather than the consent of users.
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Question #2
Random forest algorithms are in what type of machine learning model?
Correct answer: C
Explanation
Random forest algorithms are classified as discriminative models. Discriminative models are used to classify data by learning the boundaries between classes, which is the core functionality of random forest algorithms. They are used for classification and regression tasks by aggregating the results of multiple decision trees to make accurate predictions. Reference: The AIGP Body of Knowledge explains that discriminative models, including random forest algorithms, are designed to distinguish between different classes in the data, making them effective for various predictive modeling tasks.
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Question #3
Each of the following actors are typically engaged in the AI development life cycle EXCEPT?
Correct answer: B
Explanation
Typically, actors involved in the AI development life cycle include data architects (who design the data frameworks), socio-cultural and technical experts (who ensure the AI system is socio-culturally aware and technically sound), and legal and privacy governance experts (who handle the legal and privacy aspects). Government regulators, while important, are not directly engaged in the development process but rather oversee and regulate the industry. Reference: AIGP BODY OF KNOWLEDGE and AI development frameworks.
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Question #4
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?
Correct answer: C
Explanation
Training underwriters on the model prior to deployment is crucial so they can apply their own judgment to the initial assessment. While AI models can streamline the process, human judgment is still essential to catch nuances that the model might miss or to account for any biases or errors in the model's decision-making process. Reference: The AIGP Body of Knowledge emphasizes the importance of human oversight in AI systems, particularly in high-stakes areas such as underwriting and loan approvals. Human underwriters can provide a critical review and ensure that the model's assessments are accurate and fair, integrating their expertise and understanding of complex cases.
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Question #5
Which of the following best defines an "AI model"?
Correct answer: D
Explanation
An AI model is best defined as a program that has been trained on a set of data to find patterns within that data. This definition captures the essence of machine learning, where the model learns from the data to make predictions or decisions. Reference: AIGP BODY OF KNOWLEDGE, which provides a detailed of AI models and their training processes.
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Question #6
According to the GDPR's transparency principle, when an AI system processes personal data in automated decision-making, controllers are required to provide data subjects specific information on?
Correct answer: A
Explanation
The GDPR's transparency principle requires that when personal data is processed for automated decision-making, including profiling, data subjects must be informed about the existence of such automated decision-making. Additionally, they must be provided with meaningful information about the logic involved, as well as the significance and the envisaged consequences of such processing for them. This requirement ensures that data subjects are fully aware of how their personal data is being used and the potential impacts, thereby promoting transparency and trust in the processing activities.
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Question #7
The OECD's Ethical AI Governance Framework is a self-regulation model that proposes to prevent societal harms by?
Correct answer: D
Explanation
The OECD's Ethical AI Governance Framework aims to ensure that AI development and deployment are carried out ethically while fostering innovation. The framework includes principles like transparency, accountability, and human rights protections to prevent societal harm. It does not focus solely on technical design or post-deployment monitoring (C), nor does it establish industry-specific requirements (B). While explainability is important, the primary goal is to balance innovation with ethical considerations (D).
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Question #8
If it is possible to provide a rationale for a specific output of an AI system, that system can best be described as?
Correct answer: C
Explanation
If it is possible to provide a rationale for a specific output of an AI system, that system can best be described as explainable. Explainability in AI refers to the ability to interpret and understand the decision-making process of the AI system. This involves being able to articulate the factors and logic that led to a particular output or decision. Explainability is critical for building trust, enabling users to understand and validate the AI system's actions, and ensuring compliance with ethical and regulatory standards. It also facilitates debugging and improving the system by providing insights into its behavior.
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Question #9
All of the following may be permissible uses of an AI system under the EU AI Act EXCEPT?
Correct answer: C
Explanation
The EU AI Act explicitly prohibits the use of AI systems for social scoring by public authorities, as it can lead to discrimination and unfair treatment of individuals based on their social behavior or perceived trustworthiness. While AI can be used to promote equitable distribution of welfare benefits, manage border control, and even detect an individual's intent for law enforcement purposes (within strict regulatory and ethical boundaries), implementing social scoring systems is not permissible under the Act due to the significant risks to fundamental rights and freedoms.
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Question #10
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 .. 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. During the first month when ABC monitors the model for bias, it is most important to?
Correct answer: A
Explanation
During the first month of monitoring the model for bias, it is most important to continue disparity testing. Disparity testing involves regularly evaluating the model's decisions to identify and address any biases, ensuring that the model operates fairly across different demographic groups. Reference: Regular disparity testing is highlighted in the AIGP Body of Knowledge as a critical practice for maintaining the fairness and reliability of AI models. By continuously monitoring for and addressing disparities, organizations can ensure their AI systems remain compliant with ethical and legal standards, and mitigate any unintended biases that may arise in production.
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Discussion
Explain your reasoning, not just the letterOther IAPP certifications
- CIPP-E: Certified Information Privacy Professional/Europe (CIPP/E) (opens in a new tab)
- CIPM: Certified Information Privacy Manager (opens in a new tab)
- CIPT: Certified Information Privacy Technologist (CIPT) (opens in a new tab)
- HPE6-A84: Aruba Certified Network Security Expert Written Exam (opens in a new tab)
- CIPP-A: Certified Information Privacy Professional/Asia (CIPP/A) (opens in a new tab)
- CIPP-C: Certified Information Privacy Professional/Canada (CIPP/C) (opens in a new tab)
- CIPP-US: Certified Information Privacy Professional/United States (CIPP/US) (opens in a new tab)
- HPE6-A82: HPE Sales Certified - Aruba Products and Solutions (opens in a new tab)
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FAQ
Learn More: https://iapp.org/certify/programs/
- Q1: What is the AIGP: Artificial Intelligence Governance Professional exam?
- A: AIGP: Artificial Intelligence Governance Professional is a IAPP certification exam. Judging by the questions in our bank, it concentrates on police, healthcare, department, criminal and generative.
- Q2: What topics does the AIGP: Artificial Intelligence Governance Professional exam cover?
- A: Questions in our AIGP: Artificial Intelligence Governance Professional bank cluster around police, healthcare, department, criminal, generative, consultant, intends and score. Working through the full set is the quickest way to find which of these you are weakest on.
- Q3: How should I prepare for AIGP: Artificial Intelligence Governance Professional?
- A: Work through the AIGP: Artificial Intelligence Governance Professional practice questions here, checking your answer on each one, then sit the practice test to rehearse the exam under timed conditions before the real thing.
- Q4: Are these real AIGP: Artificial Intelligence Governance Professional exam questions?
- A: They are drawn from officially released past questions and from community members who have sat AIGP: Artificial Intelligence Governance Professional. Answers are verified and updated weekly.
- Q5: Where do I register for the AIGP: Artificial Intelligence Governance Professional exam?
- A: Register through IAPP directly. Exampractice is not affiliated with IAPP and does not administer the exam.
- Q6: Is there a free AIGP: Artificial Intelligence Governance Professional sample?
- A: Yes. Every AIGP: Artificial Intelligence Governance Professional page shows a free sample of real questions. Upgrading opens the full bank and the practice test.
- Q7: What are IAPP Certification Exams?
- A: IAPP (International Association of Privacy Professionals) Certification Exams validate your expertise in privacy and data protection. These certifications demonstrate your proficiency in managing and protecting personal data, ensuring compliance with global privacy laws and regulations.
- Q8: Why should I pursue IAPP Certification?
- A: IAPP Certification enhances your professional credibility, showcasing your skills and knowledge in privacy management. This can lead to better job opportunities, higher salaries, and career advancement in fields such as data protection, compliance, and information security.
- Q9: What are the benefits of IAPP Certification?
- A: Benefits include recognition as a certified privacy professional, improved job performance, access to exclusive resources, continuing education opportunities, and staying current with the latest privacy regulations and best practices.
- Q10: Who should take IAPP Certification Exams?
- A: Data protection officers, compliance officers, privacy professionals, IT security experts, and anyone involved in managing and protecting personal data should consider these certifications to validate their expertise and advance their careers.
- Q11: What types of IAPP Certification Exams are available?
- A: IAPP offers various certification paths, including:
- Q12: How do I prepare for IAPP Certification Exams?
- A: Preparation can include official IAPP training courses, study guides, practice exams, online tutorials, and hands-on experience in privacy management and data protection practices.
- Q13: Where can I take IAPP Certification Exams?
- A: IAPP Certification Exams can be taken online with remote proctoring or at authorized testing centers worldwide, providing flexibility to fit your schedule and location.
- Q14: How do IAPP Certifications impact my career?
- A: IAPP Certifications significantly boost your career by demonstrating your expertise to employers, making you a more competitive candidate for advanced roles and promotions in privacy management, compliance, and data protection.
- Q15: Are there any prerequisites for IAPP Certification Exams?
- A: While there are no strict prerequisites for many IAPP exams, having a foundational knowledge of privacy laws and practices or prior experience in data protection can be beneficial. Check the specific requirements for each certification path on the IAPP website.
- Q16: How often do I need to recertify for IAPP Certifications?
- A: IAPP Certifications typically require recertification every two years, which involves earning Continuing Privacy Education (CPE) credits to ensure that certified professionals stay updated with the latest privacy practices and industry standards.



