In short
CT-AI (AI Testing) covers testing AI-based systems: how do I demonstrate that a product containing machine learning works reliably? CT-GenAI (Testing with Generative AI) takes the opposite view: how do I use generative AI as a tool in the test process – productively, traceably and in line with the rules? Both belong to the Specialist stream of the ISTQB® scheme, and both exams require the CTFL certificate.
CT-AI: testing AI-based systems
The ISTQB® Certified Tester – AI Testing (CT-AI) addresses teams whose test object contains AI – say credit scoring, image recognition or a recommendation engine. The syllabus covers machine learning foundations, quality characteristics of AI-based systems such as bias, transparency and robustness, training data quality, evaluating ML models, and AI-specific test techniques and environments. Using AI to support testing is part of the syllabus too – from a classic machine learning perspective.
Typical triggers: your product makes automated decisions, business or regulators demand evidence, or QA is asked to sign off an ML feature and lacks the vocabulary for it.
CT-GenAI: testing with generative AI
The ISTQB® Certified Tester Specialist – Testing with Generative AI (CT-GenAI) is the younger of the two certificates and addresses day-to-day testing itself: Prompt-Engineering for test tasks, deriving test cases and generating test data with LLMs, verifying AI output before it goes productive, RAG and LLM agents in the test context, and governance questions up to the EU AI Act. It is aimed at testers, test managers and test automation engineers who want to bring generative AI into their work in a controlled way.
We run this seminar regularly – contents, dates in several cities and online, and booking are on the CT-GenAI seminar page.
The two certificates compared
| CT-AI | CT-GenAI | |
|---|---|---|
| Direction of view | Testing of AI-based systems | Testing with generative AI |
| Test object | the AI system in the product (ML models, data, decisions) | your software, unchanged – the AI is a tool in the test process |
| Core contents | ML foundations, bias, robustness, data quality, model evaluation, AI-specific test techniques | Prompt-Engineering, test case and test data generation, output verification, RAG/agents, governance |
| Audience | QA for products with an AI component | test teams that want to work more efficiently |
| Level in the scheme | Specialist | Specialist |
| Prerequisite | no formal entry requirement for either seminar; for each exam, ISTQB® requires the CTFL certificate | |
| At Loyal Team | currently not in the open programme – talk to us if you need it | open dates (cities + online, DE/EN) and in-house; exam through GASQ, €250 plus VAT |
Exam modalities are set by the certification bodies; the ISTQB® syllabus and exam regulations in their current version are authoritative.
Which one do you need?
- Your product contains AI (scoring, recognition, recommendations, a chatbot as a feature): CT-AI – you need to demonstrate the quality of the AI system.
- Your team should test faster and better with GenAI (test cases, test data, scripts, reviews): CT-GenAI.
- QA leads with an AI strategy: both in the medium term – start where the acute need is. In most teams today that is tool usage, i.e. CT-GenAI.
Both certificates build on the same foundation: the ISTQB® Certified Tester Foundation Level. Where the Specialist level sits in the overall scheme is shown on the career path.
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