ISTQB® CT AI Testing

The AI Testing Curriculum equips professionals with the knowledge and techniques required to test AI-based systems. It is designed to address the unique challenges and quality aspects that arise when applying machine learning and artificial intelligence in software development.

Two syllabus versions are currently examinable. You can take the CT‑AI exam based on either Syllabus v2.0 (the current version) or Syllabus v1.0, which remains available until 21 April 2027 for English exams and 21 October 2027 for exams in other languages. We recommend Syllabus v2.0 for new candidates.

This certification is ideal for professionals working in or entering fields such as software testing, data science, test management, or AI development.

Prior knowledge of AI or machine learning is helpful but not required. The CT-AI curriculum provides a balanced overview for both experienced testing professionals who want to expand their skills and individuals from data or development backgrounds seeking to understand testing in the context of AI.

Syllabus v2.0 (current version)

Syllabus v2.0 focuses on testing AI-based systems, including systems based on generative AI and large language models (LLMs). It introduces fundamental concepts such as bias, ethics, transparency, and model performance, and covers specialized testing approaches like metamorphic testing, adversarial testing, and model validation techniques. New in v2.0 is dedicated coverage of testing generative AI and LLMs, including red teaming, as well as modern topics such as pretrained models, fine-tuning, and retrieval-augmented generation (RAG).

Components

• Introduction to artificial intelligence (including generative AI)
• Quality characteristics for AI-based systems
• Machine learning (data preparation, performance metrics, and neural networks)
• Testing AI-based systems (including generative AI and large language models)
• Input data testing for machine learning systems
• Model testing for machine learning systems
• Machine learning development testing

Prerequisites

ISTQB® Certified Tester – Foundation Level (CT‑FL)

Exam Highlights

• Format: 40 multiple-choice questions
• Duration: 60 minutes + 25 % extra time for non‑native speakers (75 min)
• Passing Score: at least 65 % (29 out of 44 points)

Exam Preparation

• ISTQB CT‑AI Syllabus v2.0 ⤴
• ISTQB CT‑AI Sample Exam Questions v2.1 ⤴
• ISTQB CT‑AI Sample Exam Answers v2.1 ⤴

Syllabus v1.0 (valid until 2027)

Syllabus v1.0 covers testing AI-based systems and, in addition, using AI to support testing activities such as test generation and classification — a topic that is no longer part of v2.0. Exams (including retakes) based on Syllabus v1.0 remain available until 21 April 2027 (English) and 21 October 2027 (other languages).

Components

• Introduction to AI and machine learning concepts
• Quality characteristics of AI-based systems (e.g. bias, fairness, explainability)
• Model training, validation, and test metrics
• Test design techniques specific to AI systems
• Using AI to support test activities
• Testing environments and tool support

Prerequisites

ISTQB® Certified Tester – Foundation Level (CT‑FL) or British Computer Society (BCS) Certificate in Requirements Engineering

Exam Highlights

• Format: 40 multiple-choice questions
• Duration: 60 minutes + 25 % extra time for non‑native speakers (75 min)
• Passing Score: more than 65 % (31 out of 47 points)

Exam Preparation

• ISTQB CT‑AI Syllabus v1.0 ⤴
• ISTQB CT‑AI Sample Exam Questions v1.1 ⤴
• ISTQB CT‑AI Sample Exam Answers v1.2 ⤴