ISQI CT-GenAI Exam Details & Actual Exam 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,17 2026
  • Certification Level: Foundation

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

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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
Certificate Validity Period:Not publicly specified (typically 3-5 years depending on scheme)
Exam Duration:60 minutes
Available Languages:English, German
Related Certifications:ISTQB CTFL (Foundation Level Tester)
Exam Price:250 EUR (+ VAT)
Real Exam Qty:40
Exam Format:Multiple Choice
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:

SectionWeightObjectives
Fundamentals of Generative AI20%- AI Development Lifecycle
  • 1. Evaluation
  • 2. Model training and fine-tuning
  • 3. Data collection, preparation, and curation
  • 4. Deployment and monitoring
- AI Terminology
  • 1. Transformer architecture
  • 2. Deep Learning
  • 3. Artificial Intelligence (AI)
  • 4. Large Language Models (LLMs)
  • 5. Machine Learning (ML)
  • 6. Tokens and prompts
  • 7. Generative AI (GenAI)
- Generative AI Concepts
  • 1. Alignment and guardrails
  • 2. Emergent capabilities and limitations
  • 3. AI model behavior
  • 4. Model types (Base, Instruction-tuned, RAG)
  • 5. Training data and context windows
  • 6. Hallucinations
Risks and Testing Challenges for Generative AI30%- Testing Challenges for Generative AI
  • 1. Regulatory and compliance considerations
  • 2. Ethical testing concerns
  • 3. Coverage challenges
  • 4. Complexity of the AI component
  • 5. Subjectivity of quality assessment
  • 6. Non-deterministic output behavior
  • 7. Test oracle problem
- Quality Risks Specific to Generative AI
  • 1. Dependency on external components
  • 2. Input sensitivity (prompt brittleness)
  • 3. Incorrect or fabricated outputs (hallucinations)
  • 4. Inconsistent responses across runs
  • 5. Inappropriate output for the context
  • 6. Offensive, harmful, or biased content
Tools for Testing Generative AI20%- Testing Tools Overview
  • 1. Selecting appropriate tools for specific testing needs
  • 2. Categories of GenAI testing tools
- Using Tools for Common Testing Activities
  • 1. Simulation and monitoring tools
  • 2. Security testing tools
  • 3. Model evaluation tools
  • 4. Prompt testing tools
Testing Activities for Generative AI30%- Traceability and Documentation
  • 1. Documentation requirements for AI testing
  • 2. Test coverage of AI model components
- Requirements-Based Testing
  • 1. AI-related quality requirements
  • 2. Non-functional requirements for AI-based systems
  • 3. Functional requirements for AI-based systems
- Model and Output Evaluation
  • 1. Human evaluation methods
  • 2. Checkpoint testing
  • 3. Metamorphic testing
  • 4. Automated evaluation methods
  • 5. Output correctness and quality assessment
- Prompt-Based Testing
  • 1. Prompt engineering basics
  • 2. Test data creation with GenAI
  • 3. Test case design using prompts


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