Prepare with ISQI CT-GenAI exam practice material, pass for sure
Updated: Aug 20, 2026
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ISQI CT-GenAI Exam Overview:
| Certification Vendor: | ISQI / ASTQB |
| Exam Name: | ISTQB Certified Tester Testing with Generative AI |
| Exam Number: | CT-GenAI |
| Real Exam Qty: | 40 |
| Certificate Validity Period: | Not publicly specified (typically 3-5 years depending on scheme) |
| Available Languages: | English, German |
| Exam Format: | Multiple Choice |
| Exam Duration: | 60 minutes |
| Related Certifications: | ISTQB CTFL (Foundation Level Tester) |
| Exam Price: | 250 EUR (+ VAT) |
| Passing Score: | 65% |
| Sample Questions: | ISQI CT-GenAI Sample Questions |
| Exam Way: | Online proctored / In-person at authorized test centers |
| Pre Condition: | ISTQB CTFL (Foundation Level Tester) certification is recommended but not required |
| Official Syllabus URL: | https://www.astqb.org/ct-genai/ |
ISQI CT-GenAI Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Fundamentals of Generative AI | 20% | - AI Terminology
|
| Testing Activities for Generative AI | 30% | - Model and Output Evaluation
|
| Risks and Testing Challenges for Generative AI | 30% | - Quality Risks Specific to Generative AI
|
| Tools for Testing Generative AI | 20% | - Testing Tools Overview
|
ISQI ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0 Sample Questions:
1. 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) ii, iii, iv
B) i, iii, v
C) i, ii, iii (Duplicate entry in original source)
D) i, ii, iii
2. Who typically defines the system prompt in a testing workflow?
A) CI server automatically without human input
B) Product owner in user stories only
C) A tester configuring the assistant
D) End user during normal chat use
3. Which AI approach requires feature engineering and structured data preparation?
A) Classical Machine Learning
B) Symbolic AI
C) Deep Learning
D) Generative AI
4. What defines a prompt pattern in the context of structured GenAI capability building?
A) Maintaining static documentation repositories without real-time prompt standardization processes
B) Applying a reusable and structured template that guides GenAI models toward consistent outputs
C) Using ad hoc prompts without reference to previously proven structures or examples
D) Treating prompts as access credentials or compliance records rather than functional templates
5. Which statement BEST describes vision-language models (VLMs)?
A) VLMs are unrelated to multimodal LLMs and focus only on UI automation.
B) VLMs are a superset of multimodal LLMs.
C) VLMs are a subset of multimodal LLMs integrating visual and textual information.
D) VLMs process audio and video but not images.
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: C | Question # 3 Answer: A | Question # 4 Answer: B | Question # 5 Answer: C |
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