Try and practice the latest ISQI : CT-GenAI real questions & answers
Updated: Aug 17, 2026
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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 |
| Exam Price: | Varies by region (~230–260 EUR typical EU pricing; provider-dependent) |
| Related Certifications: | ISTQB Certified Tester Foundation Level (CTFL) |
| Passing Score: | Approximately 65% (typically 26/40 correct answers; varies slightly by board) |
| Exam Duration: | 60 (+15 min extension for non-native language candidates) |
| Real Exam Qty: | 40 multiple-choice questions |
| Certificate Validity Period: | No expiry for certification (ISTQB certifications are generally lifelong) |
| Available Languages: | English, Local language versions depending on member board |
| Recommended Training: | ISTQB Sample Exams & Resources ISTQB CT-GenAI Syllabus (Official PDF) |
| Exam Registration: | ISTQB Official Certification Portal Member Board / Exam Providers (varies by country) |
| 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:
| Section | Objectives |
|---|---|
| Organizational Adoption and Governance | - Enterprise GenAI adoption
|
| Application of GenAI in Software Testing | - Practical use in testing workflows
|
| Risk, Quality, and Limitations of GenAI | - Risks in GenAI usage
|
| Foundations of Generative AI and LLMs | - Introduction to Generative AI in Software Testing
|
| Prompt Engineering for Testing | - Prompt design techniques
|
ISQI ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0 Sample Questions:
1. Which technique MOST directly reduces hallucinations by grounding the model in project realities?
A) Provide detailed context
B) Randomize prompts each run
C) Rely on generic examples only
D) Use longer temperature settings
2. Which consideration BEST aligns LLM choice with organizational goals in a GenAI testing strategy?
A) Select models with maximum vendor visibility and strong online presence to ensure reliability
B) Select LLMs aligned to measurable test outcomes, compatible with current infrastructure
C) Select broad-coverage models offering diverse functionalities for various test scenarios
D) Select open-source models prioritizing creativity over compliance or performance consistency
3. In the context of software testing, which statements (i-v) about foundation, instruction-tuned, and reasoning LLMs are CORRECT?
i. Foundation LLMs are best suited for broad exploratory ideation when test requirements are underspecified.
ii. Instruction-tuned LLMs are strongest at adhering to fixed test case formats (e.g., Gherkin) from clear prompts.
iii. Reasoning LLMs are strongest at multi-step root-cause analysis across logs, defects, and requirements.
iv. Foundation LLMs are optimal for strict policy compliance and template conformance.
v. Instruction-tuned LLMs can follow stepwise reasoning without any additional training or prompting.
A) i, ii, iii (Duplicate entry in original source)
B) i, iii, v
C) i, ii, iii
D) ii, iii, iv
4. Which statement about fine-tuning for test tasks is INCORRECT?
A) It enhances relevance to organizational terminology and formats
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 replaces the model's general knowledge entirely and prevents overfitting
5. Your team needs to generate 500 API test cases for a REST API with 50 endpoints. You have documented 10 exemplar test cases that follow your organization's standard format. You want the LLM to generate test cases following the pattern demonstrated in your examples. Which of the following prompting techniques is BEST suited to achieve your goal in this scenario?
A) Meta prompting
B) Few-shot prompting
C) Zero-shot prompting
D) Prompt chaining
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: B | Question # 3 Answer: C | Question # 4 Answer: D | Question # 5 Answer: B |
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