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Updated: Aug 19, 2026
No. of Questions: 42 Questions & Answers with Testing Engine
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| Certification Vendor: | ISQI / ASTQB |
| Exam Name: | ISTQB Certified Tester Testing with Generative AI |
| Exam Number: | CT-GenAI |
| Exam Format: | Multiple Choice |
| Real Exam Qty: | 40 |
| Exam Price: | 250 EUR (+ VAT) |
| Available Languages: | English, German |
| Exam Duration: | 60 minutes |
| Passing Score: | 65% |
| Related Certifications: | ISTQB CTFL (Foundation Level Tester) |
| Certificate Validity Period: | Not publicly specified (typically 3-5 years depending on scheme) |
| 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/ |
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Risks and Testing Challenges for Generative AI | 30% | - Testing Challenges for Generative AI
|
| Topic 2: Tools for Testing Generative AI | 20% | - Using Tools for Common Testing Activities
|
| Topic 3: Fundamentals of Generative AI | 20% | - Generative AI Concepts
|
| Topic 4: Testing Activities for Generative AI | 30% | - Requirements-Based Testing
|
1. You are using an LLM to assist in analyzing test execution trends to predict potential risks. Which of the following improvements would BEST enhance the LLM's ability to predict risks and provide actionable alerts?
A) Specify that the role is a test analyst with expertise in predictive analytics and risk management.
B) Expand the output format to include risk predictions with severity levels, recommended actions, and a timeline for team intervention based on trend analysis.
C) Emphasize constraints that focus on deviations that could impact release timelines or quality gates.
D) Add an instruction to calculate statistical variance and highlight tests that deviate by more than 20% from baseline metrics.
2. Which AI approach requires feature engineering and structured data preparation?
A) Symbolic AI
B) Classical Machine Learning
C) Deep Learning
D) Generative AI
3. Who typically defines the system prompt in a testing workflow?
A) End user during normal chat use
B) CI server automatically without human input
C) A tester configuring the assistant
D) Product owner in user stories only
4. What distinguishes an LLM-powered agent from a basic AI chatbot in test processes?
A) Ability to respond to prompts without explicit user instructions
B) Reliance on predefined templates to generate short, factual answers
C) Use of a conversational tone and improved response personalization
D) Ability to trigger automated actions beyond conversation
5. Which concept refers to breaking text into smaller units for processing by LLMs?
A) Tokenization
B) Embeddings
C) Transformer
D) Context Window
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: B | Question # 3 Answer: C | Question # 4 Answer: D | Question # 5 Answer: A |
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