Overview
It not only explains the fundamentals of GenAI but also builds practical skills through real-world prompt-engineering patterns and applied testing use cases. Testers will learn how to integrate GenAI capabilities responsibly while managing key risks such as hallucinations, bias, security, privacy, and environmental impact.
The ISTQB® Certified Tester – Testing with Generative AI (CT‑GenAI) is the official ISTQB® certification for AI-powered software testing. It equips professionals to apply Generative AI (GenAI), Large Language Models (LLMs), and AI testing tools across the entire software testing process. This globally recognized ISTQB® CT-GenAI certification is designed for anyone who wants to:
- Generate test cases, acceptance criteria, and synthetic test data using AI
- Use prompt engineering techniques to improve test accuracy and automation
- Identify and mitigate AI-specific risks such as hallucinations, bias, and data privacy breaches
- Integrate LLM-powered infrastructure (RAG, LLMOps, AI agents) into test environments
- Plan and execute an organizational AI testing strategy
By earning the CT‑GenAI certification, you gain international recognition as a specialist in AI in software testing. Whether you’re new to AI or experienced in testing, this certification shows employers you can apply GenAI in practical, real-world test scenarios.
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.
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 strategy and roadmap for software testing within an organization
What are the benefits of the ISTQB® CT GenAI certification?
1. Boost your AI testing expertise
- Understand LLMs, tokenization, embeddings, and multimodal models
- Use prompt engineering (structured prompts, chaining, few-shot, meta) across all testing activities
- Generate, refine, and evaluate test cases, acceptance criteria, synthetic data, and test reports
2. Mitigate AI-specific risks
- Identify and manage hallucinations, bias, non-determinism, privacy, and security risks
- Apply ethical and regulatory best practices
- Assess the environmental impact of AI in testing
3. Adopt an AI-powered test infrastructure
- Implement RAG, fine-tuning, and LLMOps for test optimization
- Use AI agents to automate test processes
4. Lead GenAI adoption in test organizations
- Plan a GenAI adoption roadmap
- Build AI capabilities in test teams
- Adapt testing processes for AI-enabled organizations
Who should take this certification?
This certification is for professionals involved in or impacted by AI-enabled software testing, including:
- Testers, test analysts, test engineers, test automation engineers, UAT testers, test managers
- Software developers involved in testing
- Project managers, quality managers, software development managers, business analysts, IT directors, consultants
What are the entry requirements?
- To gain this certification, candidates must hold the Certified Tester Foundation Level v4.0 or previous versions of the Foundation Level certificate
- No programming experience required: suitable for both technical and non-technical roles
Training and Exam Duration
Training: 2 days
The course material shall be issued on the first day of the course during registration.
Exam: 60 minutes (+25% extra for non-native English speakers)
Exam Pattern
No. of Questions: 40
Total Points: 46
Candidates must score 30 out of 46 (65%) or greater to pass the exam.
Course Outline
1. Introduction to GenAI for Software Testing
- GenAI Foundations and Key Concepts
- Leveraging GenAI in Software Testing: Core Principles
2. Prompt Engineering for Effective Software Testing
- Effective Prompt Development
- Applying Prompt Engineering Techniques
- Evaluate GenAI Results and Refine Prompts
3. Managing Risks of GenAI in Software Testing
- Hallucinations, Reasoning Errors and Biases
- Data Privacy and Security Risks
- Energy Consumption and Environmental Impact of GenAI
- AI Regulations, Standards and Best Practice Frameworks
4. LLM-Powered Solutions for Software Testing
- Architectural Approaches for LLM-Powered Testing Solutions
- Fine-Tuning and LLMOps: Operationalizing GenAI
5. Deploying and Integrating GenAI in Test Organizations
- Roadmap for Adoption of GenAI
- Manage Change when Adopting GenAI
