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  • Exam Code: CT-GenAI
  • Exam Name: ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0
  • No. of Questions: 42 Questions and Answers
  • Updated: Sep 11, 2026
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ISQI CT-GenAI Exam Syllabus Topics:

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

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

What is a hallucination in LLM outputs?

  • A. A systematic preference learned from data
  • B. A logical mistake in multi-step deduction
  • C. A transient network failure during inference
  • D. Generation of factually incorrect content for the task
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

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When an organization uses an AI chatbot for testing, what is the PRIMARY LLMOps concern?

  • A. Focusing primarily on user experience improvements and response formatting
  • B. Maintaining data privacy and minimizing security risks from external services
  • C. Maximizing scalability by deploying larger cloud-based LLM clusters
  • D. Achieving faster responses by reducing model checkpoints and updates
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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Which statement about data privacy risks in GenAI-assisted testing is INCORRECT?

  • A. Some GenAI tools may store/process data without explicit consent
  • B. Strict GDPR compliance eliminates all privacy risk
  • C. Using GenAI without regulatory compliance can lead to legal exposure
  • D. GenAI outputs can accidentally reveal sensitive information present in inputs
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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Which consideration BEST aligns LLM choice with organizational goals in a GenAI testing strategy?

  • A. Select broad-coverage models offering diverse functionalities for various test scenarios
  • B. Select open-source models prioritizing creativity over compliance or performance consistency
  • C. Select LLMs aligned to measurable test outcomes, compatible with current infrastructure
  • D. Select models with maximum vendor visibility and strong online presence to ensure reliability
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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Which standard specifies requirements for managing AI systems within an organization, supporting consistent GenAI use in testing?

  • A. NIST AI RMF 1.0
  • B. EU AI Act
  • C. ISO/IEC 23053:2022
  • D. ISO/IEC 42001:2023
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

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