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| Section | Weight | Objectives |
|---|---|---|
| Governance of AI Deployment and Use | 21–25% | - Selection, procurement and third-party management - Implementation, monitoring and ongoing oversight - Lifecycle maintenance, decommissioning and updates - Incident response, accountability and audit |
| Laws, Regulations, Standards and Frameworks | 24–28% | - Sector-specific requirements and compliance obligations - International standards (ISO 42001, NIST AI RMF, etc.) - Alignment with data protection and privacy laws - Global and regional regulations (EU AI Act, US, etc.) |
| Governance of AI Development | 21–25% | - Model management, version control and quality assurance - Governance through design and lifecycle management - Testing, validation, documentation and transparency - Requirements gathering, risk assessment and mitigation |
| Foundational Concepts of AI Governance | 24–28% | - Principles of responsible, ethical and trustworthy AI - Fundamental AI definitions, types and characteristics - Governance frameworks and core concepts - Impacts, risks and benefits of AI systems |
>> Latest AIGP Exam Answers <<
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NEW QUESTION # 30
All of the following may be copyright risks from teachers using generative AI to create course content EXCEPT?
Answer: D
Explanation:
The correct answer is C. This option concerns consent, which is generally a privacy, transparency, or institutional governance issue rather than a copyright issue. Copyright risk in AI governance usually relates to whether protected third party works were used in model training, whether generated outputs may reproduce copyrighted expression, and whether content is created without proper attribution or clear ownership boundaries. That makes options A, B, and D directly relevant to copyright and intellectual property concerns. In contrast, whether students must expressly consent deals with notice, fairness, and lawful or ethical use in an educational environment. For AIGP exam purposes, it is important to separate intellectual property risks from privacy and data protection obligations, even when both appear in the same classroom or organizational AI use case.
NEW QUESTION # 31
After initially deploying a third-party AI model, you learn the developer has released a new version.
As deployer of this third-party model, what should you do?
Answer: A
Explanation:
When anew versionof a third-party model is released, the deployer must ensure it still meets safety, performance, and compliance requirements - which calls for aformal audit.
From theAI Governance in Practice Report2025:
"Any updates or changes to AI systems should trigger a re-evaluation to ensure continued compliance and performance." (p. 12)
"Post-market monitoring includes reassessing the impact of updated models or retraining." (p. 35)
NEW QUESTION # 32
Scenario:
A global organization wants to align with international frameworks on AI governance. They are reviewing guidance from the OECD on how to incorporate broader governance tools into their AI program.
Codes of conductandcollective agreementsare what type of assessment tools as defined by theOrganization for Economic Cooperation and Development (OECD)?
Answer: B
Explanation:
The correct answer isB - Procedural. TheOECD Framework for Classifying AI Systemscategorizescodes of conduct and collective agreementsasprocedural toolsbecause they guide internal governance and decision- making processes.
From the AIGP ILT Participant Guide - Global Governance Models:
"Procedural tools include internal codes of conduct, collective agreements, and procedural audits that guide governance without necessarily involving technical measurement." AI Governance in Practice Report2025elaborates:
"These procedural tools support internal accountability mechanisms and ethics compliance frameworks...
they are part of soft governance."
These toolsdo not measure or analyze technical performance, hence they arenot technical or analytic.
NEW QUESTION # 33
An AI system's function, the industry and the location in which it operates are important factors in considering which of the following?
Answer: D
Explanation:
An AI system'sfunction,industry, anddeployment locationdefine itsrisk profile, which directly influences theinternal governance structuresan organization must put in place.
From theAI Governance in Practice Report 2024:
"There are many challenges and potential solutions for AI governance, each with unique proximityand significance based on an organization's role, footprint, broader risk-governance profile and maturity." (p. 4)
"AI governance starts with defining the corporate strategy for AI... and formulating policy standards and operational procedures to reflect industry, use case, and location." (p. 11)
* A- Organizational accountability is broader and not directly scoped by industry or function.
* C- Diversity of data sources is tied to data strategy.
* D- Explainability is more influenced by model type, not use context.
NEW QUESTION # 34
What is a primary liability concern when a company deploys a proprietary Agentic AI model?
Answer: D
Explanation:
The correct answer is A because deploying a proprietary agentic AI model places direct responsibility on the organization for the actions and outcomes of that system. AI governance frameworks emphasize accountability as a core principle, meaning organizations must take responsibility for harms caused by their AI systems, including misleading, biased, or unsafe outputs. Agentic AI systems, which can act autonomously and make decisions, introduce heightened liability risks because their behavior may directly impact users or third parties. Regulatory approaches increasingly focus on ensuring that deployers cannot shift responsibility, especially when the system is proprietary and under their control. The other options relate to operational or technical considerations, not primary legal liability. Ensuring accountability for AI behavior is central to compliance, risk management, and maintaining trust.
NEW QUESTION # 35
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