ISTQB Certified Tester AI Testing (CT-AI) Course Overview

The world of software testing is evolving rapidly, and artificial intelligence is at the center of this transformation. As AI systems become more prevalent in everything from mobile apps to critical infrastructure… you might be wondering if your current testing skills are enough.

Here's the reality: 74% of IT professionals worry that AI tools will make many of their day-to-day skills obsolete, and 69% of IT pros believe they are at risk of being replaced by AI. 96% say they are prioritizing staying up to date with AI skills to ensure better job security.

But here's what many testers don't realize – AI won't eliminate testing jobs. It'll just change what skills you need to succeed.

That's where the ISTQB AI testing certification comes in. And when you're ready to take this critical step in your career, Koenig Solutions leads the way as your trusted training partner, offering comprehensive ISTQB certification programs with over 30 years of experience in delivering world-class IT certifications.

What Is ISTQB AI Testing Certification?

The ISTQB® AI Testing (CT-AI) certification extends understanding of artificial intelligence and/or deep (machine) learning, most specifically testing AI-based systems and using AI in testing.

Think of it this way: traditional software testing is like checking a recipe. You know the ingredients, you follow specific steps, and you can predict the outcome. But AI systems? They're more like teaching someone to cook intuitively – they learn, adapt, and sometimes surprise you with results you didn't expect.

The Certified Tester AI Testing certification is aimed at anyone involved in testing AI-based systems and/or AI for testing. This includes people in roles such as testers, test analysts, data analysts, test engineers, test consultants, test managers, user acceptance testers, and software developers. This certification is also appropriate for anyone who wants a basic understanding of testing AI-based systems and/or AI for testing, such as project managers, quality managers, software development managers, business analysts, operations team members, IT directors, and management consultants.

Why This Certification Matters More Than Ever

The numbers don't lie about the urgency of AI skills. Nearly 1 in 4 U.S. tech jobs posted so far this year are seeking employees with artificial-intelligence skills, job-listings data show, as companies in nearly every corner of the economy adjust their recruiting pipelines to embrace the technology.

ISTQB AI Testing certification is a career must-have for everyone who may test AI-based systems or is using AI for testing. The certified tester artificial intelligence ISTQB program is becoming essential as organizations worldwide recognize that traditional testing approaches simply don't work for AI systems.

What You'll Learn and Master

The certified tester artificial intelligence ISTQB program isn't just about passing an exam. It's about building skills that matter in today's testing landscape.

The expected business outcomes for candidates who achieve the Certified Tester AI Testing certification are · Understand the current state and expected trends of AI · Experience the implementation and testing of a ML model and recognize where testers can best influence its quality · Understand the challenges associated with testing AI-Based systems, such as their self-learning capabilities, bias, ethics, complexity, non-determinism, transparency and explainability · Contribute to the test strategy for an AI-Based system.

Key Skills You'll Develop

AI System Testing Fundamentals

• Understanding how AI systems behave differently from traditional software

• Recognizing when deterministic testing approaches won't work

• Identifying unique quality characteristics of AI systems

Machine Learning Model Testing
Design tests tailored for machine learning models. Validate training data for bias, noise, and imbalance. Collaborate effectively with developers and data scientists.

Risk Assessment and Ethics Identify risks like bias and non-deterministic AI behavior. Support ethical AI and regulatory compliance.