ISQI CT-GenAI Exam Information and Actual Questions

  • Exam Code/Number: CT-GenAI
  • Exam Name/Title: ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0
  • Certification Provider: ISQI
  • Corresponding Certification: AI Testing
  • Exam Questions: 42
  • Updated On: Jul 13, 2026

CT-GenAI
FREE EXAM DUMPS QUESTIONS & ANSWERS

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

View CT-GenAI actual exam questions, answers and explanations for free.

Go To CT-GenAI Questions

All the information you need to pass ISQI ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0 CT-GenAI exam and free practice exam verified by ExamDiscuss exam experts.

ISQI CT-GenAI Exam Overview:

Certification Vendor:ISTQB® / iSQI (International Software Quality Institute) / Member Boards
Exam Name:Certified Tester Testing with Generative AI (CT-GenAI)
Exam Number:CT-GenAI v1.0
Exam Format:Multiple-choice, Single-answer questions, Scenario-based comprehension questions
Certificate Validity Period:No expiry for certification (ISTQB certifications are generally lifelong)
Exam Price:Varies by region (~230–260 EUR typical EU pricing; provider-dependent)
Available Languages:English, Local language versions depending on member board
Related Certifications:ISTQB Certified Tester Foundation Level (CTFL)
Exam Duration:60 (+15 min extension for non-native language candidates)
Passing Score:Approximately 65% (typically 26/40 correct answers; varies slightly by board)
Real Exam Qty:40 multiple-choice questions
Sample Questions:ISQI CT-GenAI Sample Questions
Exam Way:Online proctored or test center (Pearson VUE / ISTQB member boards depending on region)
Pre Condition:ISTQB Certified Tester Foundation Level (CTFL) is required
Official Syllabus URL:https://www.istqb.org/certifications/gen-ai/

ISQI CT-GenAI Exam Syllabus Topics:

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


                                  0
                                  0
                                  0
                                  10