Certified Tester – Testing with Generative AI (CT-GenAI)
Overview
The updated of the ISTQB® Certified Tester – Testing with Generative AI (CT-GenAI) syllabus builds upon the strong foundation established in version 1.0, further enhancing its practical relevance to today’s rapidly evolving AI-driven testing landscape.
Expanding on the original concepts, the updated syllabus provides testing and quality-engineering professionals with a more comprehensive and market-aligned learning path for effectively applying Large Language Models (LLMs) and Generative AI techniques across the entire testing lifecycle — from requirements analysis and test design to automation, reporting, and continuous improvement.
The enhanced syllabus places greater emphasis on real-world industry applications, advanced prompt-engineering practices, and emerging AI-assisted testing use cases that reflect current market demands. In addition to strengthening core GenAI fundamentals, version 1.1 equips testers with practical strategies for responsible AI adoption, including the management of risks such as hallucinations, bias, security, privacy, and environmental impact.
Audience
The qualification is intended for anyone involved in using generative AI for software testing, including testers, test analysts, test automation engineers, test managers, user-acceptance testers and software developers. It is equally valuable to professionals who need a solid understanding of GenAI in testing—project managers, quality managers, software development managers, business analysts, IT directors and consultants.
Content
ISTQB® Certified Tester – Testing with Generative AI (CT-GenAI)
Introduction to GenAI for Software Testing
GenAI Foundations and Key Concepts
Leveraging GenAI in Software Testing: Core Principles
Prompt Engineering for Effective Software Testing
Effective Prompt Development
Applying Prompt Engineering Techniques
Evaluate GenAI Results and Refine Prompts
Managing Risks of GenAI in Software Testing
Process
Hallucinations, Reasoning Errors and Biases
Data Privacy and Security Risks
Energy Consumption and Environmental Impact of GenAI
AI Regulations, Standards and Best Practice Frameworks
LLM-Powered Solutions for Software Testing
Architectural Approaches for LLM-Powered Testing Solutions
Fine-Tuning and LLMOps: Operationalizing GenAI
Deploying and Integrating GenAI in Test Organizations
Roadmap for Adoption of GenAI
Manage Change when Adopting GenAI
Exam Structure
- No. of Questions: 40
- Passing Score: 30 (65%)
- Total Points: 46
- Exam Length (mins): 60 (+25% Non-Native Language)
Business Outcomes
A candidate who has achieved the CT-GenAI certification should be able to:
- Understand the fundamental concepts, capabilities, and limitations of generative AI
- Develop practical skills in prompting large language models for software testing
- Gain insight into the risks and mitigations of using generative AI for software testing
- Gain insight into the applications of generative AI solutions for software testing
- Contribute effectively to the definition and implementation of a generative AI strategyand roadmap for software testing within an organization
More Information
Training & self-study – Courses will be offered by ISTQB®-accredited Training Providers (face-to-face, virtual or e-learning). Candidates may also prepare via self-study using the official syllabus and recommended references.
Prerequisite – Before taking the CT-GenAI exam, you must be certified ISTQB® Certified Tester Foundation Level (CTFL). Next steps in the career path – CT-GenAI holders can continue along the ISTQB® scheme to Core Advanced modules (Test Analyst, Technical Test Analyst, Test Manager, Test Engineering) and, later, Expert Level certifications.
