Free CompTIA AI-Essentials Practice Exam Questions and Answers 2026

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Total 251 Questions | Updated On: Apr 07, 2026

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Question 1

A healthcare AI model trained on adult patient data performs poorly when deployed in pediatric clinics. What fundamental issue does this scenario reveal?

A : Data normalization failure

B : Overfitting to noisy labels

C : Poor generalization across demographic domains

D : Redundant feature extraction

Answer: C

Question 2

An insurance company rolls out a claims processing AI tool across regional offices. In some regions, staff find the tool ineffective due to varying policy rules and data entry standards. Which AI adoption challenges are evident here?

A : Limited bandwidth

B : Lack of localization

C : Input heterogeneity

D : Ambiguous labeling

Answer: B,C

Question 3

A research lab is developing an AI model to generate realistic images from noise. Which type of AI model is best suited for this task?

A : Clustering model, since it groups similar images based on shared characteristics

B : Diffusion model, as it gradually refines random noise into high-quality images through iterative transformations

C : Discriminative model, as it classifies images into predefined categories based on labeled training data

D : Decision tree, as it organizes image features into a hierarchical structure for better categorization

Answer: B

Question 4

An autonomous drone adjusts its flight path in real time by receiving rewards for efficient navigation and penalties for collisions. Which learning paradigm does this exemplify?

A : Supervised Learning

B : Unsupervised Learning

C : Semi-Supervised Learning

D : Reinforcement Learning

Answer: D

Question 5

A financial services firm is using AI to evaluate creditworthiness, but regulators are concerned about potential bias in loan approvals. What technique should be applied to ensure fairness in AI-driven decisions?

A : Hyperparameter Tuning, as adjusting parameters improves fairness in decision outcomes

B : Bias Mitigation, as it focuses on identifying and reducing unfair treatment in AI models

C : Feature Engineering, as modifying input features ensures a fair credit evaluation

D : Model Compression, since optimizing AI model size improves efficiency and fairness

Answer: B

Page: 1 / 51

Total 251 Questions | Updated On: Apr 07, 2026

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