ISTQB CT-AI v2.0 vs v1.0: Complete Comparison & New Features Every AI Tester Should Know

2026-06-27 · Source: Artificial Intelligence on Medium · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering, Cybersecurity & Data Privacy · Depth: Intermediate, short

Summary

The ISTQB Certified Tester AI Testing (CT-AI) v2.0 syllabus has been released, significantly updating the 2021 v1.0 version to address the rapid evolution of AI. This new syllabus shifts focus from traditional machine learning testing to modern AI applications, including Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) systems, and Agentic AI. Key additions in v2.0 cover Generative AI concepts like Foundation Models and Transformers, LLM testing methodologies for hallucination and bias detection, RAG fundamentals, and Red Teaming techniques for prompt injection and jailbreak testing. Furthermore, v2.0 expands AI Quality Standards with ISO/IEC 25059 and emphasizes fairness, explainability, and trustworthiness, while reducing focus on "AI for Testing" topics like AI-based test case generation.

Key takeaway

For AI Test Engineers aiming to remain current, understanding the ISTQB CT-AI v2.0 updates is crucial. This new syllabus equips you with skills for testing modern Generative AI, LLMs, RAG, and Agentic AI systems, including critical Red Teaming techniques. Prioritize acquiring expertise in these areas to align your capabilities with current industry demands and pursue specialized roles like Generative AI Tester or LLM Validation Specialist.

Key insights

The ISTQB CT-AI v2.0 syllabus updates AI testing to encompass modern Generative AI, LLMs, RAG, and Agentic AI, moving beyond traditional ML.

Principles

• AI testing must adapt to Generative AI.
• Modern AI requires new security testing.
• AI quality standards are expanding.

In practice

• Test ChatGPT, Gemini, Copilot applications.
• Validate enterprise RAG solutions.
• Apply Red Teaming for AI security.

Topics

• ISTQB CT-AI v2.0
• Generative AI Testing
• Large Language Models
• Retrieval-Augmented Generation
• AI Security
• Red Teaming

Best for: AI Engineer, Machine Learning Engineer, Software Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by Artificial Intelligence on Medium.