- A
Cloud infrastructure configuration
Why wrong: Infrastructure is operational, not governance.
- B
Model accuracy benchmarks
Why wrong: Accuracy is evaluated during development, not a governance component.
- C
Risk assessment and mitigation plans
Essential for identifying and managing AI risks.
- D
Transparency and explainability policies
Required for accountability and trust.
- E
Data management and privacy controls
Ensures data quality and regulatory compliance.
Question 189 of 1,000
Key Components of an AI Governance Framework
This AI0-001 practice question tests your understanding of ai security, ethics and governance. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Which THREE of the following are key components of an AI governance framework?
Quick Answer
The correct answer is risk assessment, data management and privacy controls, and transparency. These three are key components of an AI governance framework because governance focuses on the policies and processes that ensure ethical, legal, and responsible AI use, not on technical performance or deployment specifics. Risk assessment identifies potential harms and biases, data management governs how data is collected, stored, and used with privacy controls, and transparency ensures decisions are explainable and auditable. On the CompTIA AI+ AI0-001 exam, this question tests your ability to distinguish governance pillars from operational metrics or infrastructure—a common trap is confusing model accuracy, which measures performance, with governance, which oversees accountability. Similarly, cloud infrastructure is a deployment choice, not a governance component. To remember, think of the three G’s: Governance requires Guardrails (risk), Guidance (data/privacy), and Glass (transparency).
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Risk assessment and mitigation plans
Option C is correct because risk assessment and mitigation plans are a core component of an AI governance framework, ensuring that potential harms, biases, and security vulnerabilities are identified and addressed before deployment. This aligns with frameworks like NIST AI RMF, which mandates continuous risk monitoring and mitigation strategies to maintain ethical and secure AI operations.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Cloud infrastructure configuration
Why it's wrong here
Infrastructure is operational, not governance.
- ✗
Model accuracy benchmarks
Why it's wrong here
Accuracy is evaluated during development, not a governance component.
- ✓
Risk assessment and mitigation plans
Why this is correct
Essential for identifying and managing AI risks.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Transparency and explainability policies
Why this is correct
Required for accountability and trust.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Data management and privacy controls
Why this is correct
Ensures data quality and regulatory compliance.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
CompTIA often tests the distinction between governance (policies, ethics, risk) and operational/technical components (infrastructure, model tuning), so candidates mistakenly select cloud configuration or accuracy benchmarks as governance elements.
Detailed technical explanation
How to think about this question
An AI governance framework typically includes policies for transparency, explainability, data privacy, and risk management, as outlined in standards like ISO/IEC 42001 or the EU AI Act. Under the hood, risk assessment involves mapping AI system lifecycle stages to potential failure modes (e.g., data poisoning, drift, bias amplification) and implementing controls such as adversarial testing or fairness audits. In practice, a healthcare AI system might require a risk mitigation plan for patient data leakage, enforced through differential privacy and access control policies.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A practitioner preparing for the AI0-001 exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this AI0-001 question test?
AI Security, Ethics and Governance — This question tests AI Security, Ethics and Governance — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Risk assessment and mitigation plans — Option C is correct because risk assessment and mitigation plans are a core component of an AI governance framework, ensuring that potential harms, biases, and security vulnerabilities are identified and addressed before deployment. This aligns with frameworks like NIST AI RMF, which mandates continuous risk monitoring and mitigation strategies to maintain ethical and secure AI operations.
What should I do if I get this AI0-001 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Same concept, more angles
2 more ways this is tested on AI0-001
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. Which TWO of the following are essential components of a responsible AI governance framework?
easy- ✓ A.Assignment of a responsible owner for each AI system's outcomes
- B.Using ensemble methods to reduce overfitting
- ✓ C.Clear documentation of model development and decision-making processes
- D.Automated hyperparameter tuning to improve accuracy
- E.Deploying models on dedicated hardware to reduce latency
Why A: Option A is correct because assigning a responsible owner for each AI system's outcomes ensures accountability, which is a core principle of AI governance. This owner is typically a designated individual or team that oversees the system's lifecycle, including monitoring for bias, compliance with regulations, and handling incidents. Without clear ownership, there is no single point of contact for ethical or legal issues, making governance ineffective.
Variation 2. Which THREE of the following are key components of an AI governance framework?
medium- ✓ A.Regular auditing and monitoring for compliance.
- B.Cloud-based deployment for scalability.
- ✓ C.Ethical guidelines for AI development and deployment.
- ✓ D.Explainability mechanisms for model decisions.
- E.Model accuracy thresholds for production deployment.
Why A: Regular auditing and monitoring for compliance (A) is a key component of an AI governance framework because it ensures that AI systems operate within legal, ethical, and organizational policies over time. Continuous monitoring detects drift, bias, or security violations, while audits provide evidence of adherence to standards such as ISO/IEC 42001 or internal governance rules. Without this, governance becomes a static policy with no enforcement or verification.
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Last reviewed: Jul 4, 2026
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