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Updated: Aug 21, 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 Price: | 250 EUR (+ VAT) |
| Related Certifications: | ISTQB CTFL (Foundation Level Tester) |
| Exam Duration: | 60 minutes |
| Available Languages: | English, German |
| Exam Format: | Multiple Choice |
| Passing Score: | 65% |
| Real Exam Qty: | 40 |
| 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: Fundamentals of Generative AI | 20% | - Generative AI Concepts
|
| Topic 2: Tools for Testing Generative AI | 20% | - Testing Tools Overview
|
| Topic 3: Testing Activities for Generative AI | 30% | - Traceability and Documentation
|
| Topic 4: Risks and Testing Challenges for Generative AI | 30% | - Quality Risks Specific to Generative AI
|
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) Emphasize constraints that focus on deviations that could impact release timelines or quality gates.
C) Expand the output format to include risk predictions with severity levels, recommended actions, and a timeline for team intervention based on trend analysis.
D) Add an instruction to calculate statistical variance and highlight tests that deviate by more than 20% from baseline metrics.
2. Which factor MOST influences the overall energy consumption of a Generative AI model used in software testing tasks?
A) The duration of user sessions primarily affects latency but not power efficiency
B) The number of tokens processed directly determines the carbon intensity of each query
C) The type of cloud platform affects processing speed but not total energy draw
D) The location of the data center determines model bias and accuracy levels
3. You must generate test cases for a new payments rule. The system includes API specifications stored in a vector database and prior tests in a relational database. Which of the following sequences BEST represents the correct order for applying a Retrieval-Augmented Generation (RAG) workflow?
i. Retrieve semantically similar specification chunks from the vector database ii. Feed both retrieved datasets as context for the LLM to generate new test cases iii. Retrieve relevant historical cases from the relational database iv. Submit a focused query describing the new test requirement
A) iv -> iii -> i -> ii
B) iv -> i -> iii -> ii
C) iii -> iv -> i -> ii
D) i -> iv -> iii -> ii
4. What BEST protects sensitive test data at rest and in transit?
A) Enforce role-based access controls
B) Use public file shares with read-only links
C) Rely on obfuscation instead of encryption
D) Disable TLS and rely on VPN only
5. What distinguishes an LLM-powered agent from a basic AI chatbot in test processes?
A) Reliance on predefined templates to generate short, factual answers
B) Ability to trigger automated actions beyond conversation
C) Use of a conversational tone and improved response personalization
D) Ability to respond to prompts without explicit user instructions
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: B | Question # 3 Answer: B | Question # 4 Answer: A | Question # 5 Answer: B |
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