ISQI CT-GenAI exam dumps : ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0

  • Exam Code: CT-GenAI
  • Exam Name: ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0
  • Updated: Sep 12, 2026     Q & A: 42 Questions and Answers

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ISQI CT-GenAI Exam Syllabus Topics:

SectionObjectives
Prompt Engineering for Testing- Prompt design techniques
  • 1. Prompt chaining and meta prompting
    • 2. Zero-shot, one-shot, few-shot prompting
      • 3. Structuring prompts for test case generation
        Risk, Quality, and Limitations of GenAI- Risks in GenAI usage
        • 1. Environmental and energy considerations
          • 2. Bias and fairness issues
            • 3. Data privacy and security concerns
              • 4. Hallucinations and reasoning errors
                Organizational Adoption and Governance- Enterprise GenAI adoption
                • 1. Integration into CI/CD pipelines
                  • 2. LLMOps and governance models
                    • 3. Policy, ethics, and compliance considerations
                      Application of GenAI in Software Testing- Practical use in testing workflows
                      • 1. Test data generation and augmentation
                        • 2. Test case generation using LLMs
                          • 3. Regression suite optimization
                            • 4. Defect report analysis and summarization
                              Foundations of Generative AI and LLMs- Introduction to Generative AI in Software Testing
                              • 1. LLM basics, tokenization, context window, multimodal models
                                • 2. Difference between chatbots and LLM-based test tools

                                  ISQI ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0 Sample Questions:

                                  Question #1

                                  An LLM prioritizes tests using likelihood X impact but ranks a trivial tooltip change above a payment failure.
                                  What defect does this MOST LIKELY show?

                                  • A. No defect; this is acceptable
                                  • B. Dataset bias toward UI features
                                  • C. Reasoning error in risk calculation logic
                                  • D. Hallucination
                                  Answer: C

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                                  Question #2

                                  Which statement about data privacy risks in GenAI-assisted testing is INCORRECT?

                                  • A. Strict GDPR compliance eliminates all privacy risk
                                  • B. Some GenAI tools may store/process data without explicit consent
                                  • C. GenAI outputs can accidentally reveal sensitive information present in inputs
                                  • D. Using GenAI without regulatory compliance can lead to legal exposure
                                  Answer: A

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                                  Question #3

                                  Which statement about fine-tuning for test tasks is INCORRECT?

                                  • A. It replaces the model's general knowledge entirely and prevents overfitting
                                  • B. It can be applied to smaller SLMs to improve task performance with lower compute
                                  • C. It adapts a pre-trained model to a domain using task-specific data
                                  • D. It enhances relevance to organizational terminology and formats
                                  Answer: A

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                                  Question #4

                                  Which standard specifies requirements for managing AI systems within an organization, supporting consistent GenAI use in testing?

                                  • A. EU AI Act
                                  • B. ISO/IEC 23053:2022
                                  • C. NIST AI RMF 1.0
                                  • D. ISO/IEC 42001:2023
                                  Answer: D

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                                  Question #5

                                  What does an embedding represent in an LLM?

                                  • A. Numerical vectors capturing semantic relationships
                                  • B. A set of test cases for validation
                                  • C. Tokens grouped into context windows
                                  • D. Logical rules for reasoning
                                  Answer: A

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