Try and practice the latest ISTQB : CT-AI real questions & answers

Updated: Nov 02, 2026

No. of Questions: 162 Questions & Answers with Testing Engine

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ISTQB CT-AI Exam Overview:

Certification Vendor:ISTQB
Exam Name:ISTQB Certified Tester - AI Testing
Exam Number:CT-AI
Real Exam Qty:40
Related Certifications:ISTQB CTFL
ISTQB CTAL-TTA
Exam Format:Multiple Choice
Available Languages:English
Certificate Validity Period:Lifetime (no expiration)
Exam Duration:60 minutes
Exam Price:EUR 250
Passing Score:65%
Sample Questions:ISTQB CT-AI Sample Questions
Exam Way:Online proctored or in-person at authorized testing centers
Pre Condition:ISTQB CTFL (Certified Tester Foundation Level) certification is recommended but not mandatory
Official Syllabus URL:https://www.istqb.org/certifications/artificial-intelligence-testing-certification

ISTQB CT-AI Exam Syllabus Topics:

TopicDetails
Topic 1
  • Testing AI-Specific Quality Characteristics: In this section, the topics covered are about the challenges in testing created by the self-learning of AI-based systems.
Topic 2
  • Methods and Techniques for the Testing of AI-Based Systems: In this section, the focus is on explaining how the testing of ML systems can help prevent adversarial attacks and data poisoning.
Topic 3
  • Introduction to AI: This exam section covers topics such as the AI effect and how it influences the definition of AI. It covers how to distinguish between narrow AI, general AI, and super AI; moreover, the topics covered include describing how standards apply to AI-based systems.
Topic 4
  • Test Environments for AI-Based Systems: This section is about factors that differentiate the test environments for AI-based
Topic 5
  • Using AI for Testing: In this section, the exam topics cover categorizing the AI technologies used in software testing.
Topic 6
  • Quality Characteristics for AI-Based Systems: This section covers topics covered how to explain the importance of flexibility and adaptability as characteristics of AI-based systems and describes the vitality of managing evolution for AI-based systems. It also covers how to recall the characteristics that make it difficult to use AI-based systems in safety-related applications.
Topic 7
  • ML Functional Performance Metrics: In this section, the topics covered include how to calculate the ML functional performance metrics from a given set of confusion matrices.
Topic 8
  • systems from those required for conventional systems.
Topic 9
  • Neural Networks and Testing: This section of the exam covers defining the structure and function of a neural network including a DNN and the different coverage measures for neural networks.
Topic 10
  • ML: Data: This section of the exam covers explaining the activities and challenges related to data preparation. It also covers how to test datasets create an ML model and recognize how poor data quality can cause problems with the resultant ML model.

Reference: https://www.istqb.org/certifications/artificial-inteligence-tester

ISTQB Certified Tester AI Testing Sample Questions:

Question #1

ln the near future, technology will have evolved, and Al will be able to learn multiple tasks by itself without needing to be retrained, allowing it to operate even in new environments. The cognitive abilities of Al are similar to a child of 1-2 years.' In the above quote, which ONE of the following options is the correct name of this type of Al?
SELECT ONE OPTION

  • A. General Al
  • B. Narrow Al
  • C. Super Al
  • D. Technological singularity
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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Question #2

"Splendid Healthcare" has started developing a cancer detection system based on ML. The type of cancer they plan on detecting has 2% prevalence rate in the population of a particular geography. It is required that the model performs well for both normal and cancer patients.
Which ONE of the following combinations requires MAXIMIZATION?
SELECT ONE OPTION

  • A. Maximize accuracy and recall
  • B. Maximize specificity number of classes
  • C. Maximize recall and precision
  • D. Maximize precision and accuracy
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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Question #3

Which of the following is an example of overfitting?

  • A. The model is missing relationships between the inputs and outputs
  • B. The model discards data it considers to be noise or outliers
  • C. The model is not able to generalize to accommodate new types of data
  • D. The model is too simplistic for the data
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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Question #4

An engine manufacturing facility wants to apply machine learning to detect faulty bolts. Which of the following would result in bias in the model?

  • A. Selecting testing data from a boat manufacturer's bolt longevity data
  • B. Selecting testing data from a different dataset than the training dataset
  • C. Selecting training data by purposely including all known faulty conditions
  • D. Selecting training data purposely excluding specific faulty conditions
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

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Question #5

You have been asked for your opinion on the ML approach to be used for a new age verification system. A training dataset is available with many pictures of faces and the subject's age. When new users sign up to a mobile app, they have to take a picture of their face. If the system believes they are under 18 years old it will ask them to provide a picture of their passport to prove their age. Which ONE of the following approaches do you expect to be MOST likely to succeed?

  • A. Supervised learning regression system that is re trained based on new data, including whether they provided ID that showed their age.
  • B. Supervised learning classification system that is re-trained based on new data, including whether they later provided ID that showed they were over 18.
  • C. Unsupervised learning that identifies clusters in training data that relate to people's ages.
  • D. Reinforcement learning classification system with a reward function of correct behaviour.
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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