Free Preparation Discussions
MENU
IAPP AIGP Exam Questions
- 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.
Free IAPP AIGP Exam Actual Questions
Note: Premium Questions for AIGP were last updated On Mar. 15, 2026 (see below)
A shipping service based in the US is looking to expand its operations into the EU. It utilizes an in-house developed multimodal AI model that analyzes all personal data collected from shipping senders and recipients, and optimizes shipping routes and schedules based on this data.
As they expand into the EU, all of the following descriptions should be included in the technical documentation for their AI model EXCEPT?
The EU AI Act outlines what must be included intechnical documentationfor high-risk systems. These requirements are designed to supportconformity assessment, transparency, and traceability.
From theAI Governance in Practice Report 2025:
''It mandates drawing up technical documentation... must include a general description of the AI system, the intended purpose, and a detailed description of the elements and development process.'' (p. 34)
''Documentation... includes training, testing, evaluation procedures, andappropriateness of performance metrics.'' (p. 34--35)
Therisk management systemis addressed separately through arisk management plan, not within the technical documentation itself.
Thus:
A, C, and Dare explicitly required in thetechnical documentation.
B, while important, is part of therisk management process, not a required section oftechnical documentation.
You asked a generative Al tool to recommend new restaurants to explore in Boston, Massachusetts that have a specialty Italian dish made in a traditional fashion without spinach and wine. The generative Al tool recommended five restaurants for you to visit.
After looking up the restaurants, you discovered one restaurant did not exist and two others did not have the dish.
This information provided by the generative Al tool is an example of what is commonly called?
In the context of AI, particularly generative models, 'hallucination' refers to the generation of outputs that are not based on the training data and are factually incorrect or non-existent. The scenario described involves the generative AI tool providing incorrect and non-existent information about restaurants, which fits the definition of hallucination. Reference: AIGP BODY OF KNOWLEDGE and various AI literature discussing the limitations and challenges of generative AI models.
According to the GDPR, an individual has the right to have a human confirm or replace an automated decision unless that automated decision?
According to the GDPR, individuals have the right to not be subject to a decision based solely on automated processing, including profiling, which produces legal effects or similarly significantly affects them. However, there are exceptions to this right, one of which is when the decision is based on the data subject's explicit consent. This means that if an individual explicitly consents to the automated decision-making process, there is no requirement for human intervention to confirm or replace the decision. This exception ensures that individuals can have control over automated decisions that affect them, provided they have given clear and informed consent.
CASE STUDY
A global marketing agency is adapting a large language model ("LLM") to generate content for an upcoming marketing campaign for a client's new product: a hard hat designed for construction workers of any gender to better protect them from head injuries.
The marketing agency is accessing the LLM through an application programming interface ("API") developed by a third-party technology company. They want to generate text to be used for targeted advertising communications that highlight the benefits of the hard hat to potential purchasers. Both the marketing agency and the technology company have taken reasonable steps to address Al governance.
The marketing company has:
* Entered into a contract with the technology company with suitable representations and warranties.
* Completed an impact assessment on the LLM for this intended use.
* Built technical guidance on how to measure and mitigate bias in the LLM.
* Enabled technical aspects of transparency, explainability, robustness and privacy.
* Followed applicable regulatory requirements.
* Created specific legal statements and disclosures regarding the use of the Al on its client's advertising.
The technology company has:
* Provided guidance and resources to developers to address environmental concerns.
* Build technical guidance on how to measure and mitigate bias in the LLM.
* Provided tools and resources to measure bias specific to the LLM.
* Enabled technical aspects of transparency, explainability, robustness and privacy.
* Mapped and mitigated potential societal harms and large-scale impacts.
* Followed applicable regulatory requirements and industry standards.
* Created specific legal statements and disclosures regarding the LLM. including with respect to IP and rights to data.
The technology company has also addressed environmental concerns and societal harms.
Which of the following results would be considered biased outputs from this AI system EXCEPT?
The correct answer isA. Sending ads to construction companies (business entities) rather than individual workers isa business targeting decision, not inherently a biased AI output.
From the AIGP ILT Participant Guide -- Bias & Fairness Module:
''Biased outputs often include stereotyping, exclusion of underrepresented groups, or reinforcing harmful societal assumptions.''
Examples likeinsufficient representation of minority groupsorgender-stereotyping in visuals or languageare typical manifestations of bias.
AI Governance in Practice Report 2024 also notes:
''Bias in generative models may manifest in representation gaps, stereotyping, or unequal performance across demographic groups.''
Option A, by contrast, describes adistribution strategy, not a bias generated by the AI model.
===========
Which of the following best defines an "Al model"?
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 explanation of AI models and their training processes.
- Select Question Types you want
- Set your Desired Pass Percentage
- Allocate Time (Hours : Minutes)
- Create Multiple Practice tests with Limited Questions
- Customer Support
Carmelina
4 days agoCristen
11 days agoMadonna
25 days agoHoward
1 month agoJacquline
1 month agoTheola
2 months agoRessie
2 months agoLashawnda
2 months agoSuzan
2 months agoIzetta
3 months agoJose
3 months agoValentin
3 months agoJestine
3 months agoTricia
3 months agoanderson
4 months agoBong
4 months agoCelestine
4 months agoIlene
4 months agoNathan
5 months agoOretha
5 months agoTess
5 months agoJeannine
5 months agoCherry
6 months agoJennifer
6 months agoLeota
6 months agoJustine
6 months agoHuey
9 months agoKathrine
10 months agoFrancoise
11 months agoBarrett
1 year agoMaricela
1 year agoArletta
1 year agoDoyle
1 year agoGussie
1 year agoHerminia
1 year agoKristel
1 year agoEmmett
1 year agoGladys
1 year agoLashon
1 year agoChun
1 year agoNakita
1 year agoEura
1 year agoGianna
1 year agoLetha
2 years agoIsaac
2 years agoEladia
2 years agoJoseph
2 years agoFiliberto
2 years agoLelia
2 years agoElfriede
2 years agoDerrick
2 years agoEric
2 years agoCasandra
2 years agoTess
2 years agoMaia
2 years agoLatia
2 years agoDevora
2 years ago