Artificial intelligence changes testing in two ways: AI systems need new testing approaches, and generative AI makes testing itself more efficient. Hetz Enterprises tests AI-based applications for reliability, traceability and robustness – and uses generative AI deliberately to accelerate testing.
Why AI systems are tested differently
Traditional software is deterministic: same input, same result. AI systems deliver probabilities instead of fixed answers, learn from data and do not always behave reproducibly.
That raises new questions: How do you test a system whose output can change? How do you detect bias in training data? And how does a model stay robust with unexpected input? Structured AI testing answers exactly these questions.
Testing AI systems
AI applications and machine learning models cannot be tested like traditional software. Among other things, we assess:
- functional correctness with non-deterministic behaviour
- robustness against unexpected and edge-case input
- bias and fairness in data and results
- traceability of AI decisions
- quality of training and test data
Testing with AI
Generative AI makes testing faster and more thorough. We use large language models deliberately:
- to create test cases, acceptance criteria and test data
- with prompt engineering for precise, repeatable tasks
- to spot error patterns in large data sets faster
- always with experienced testers critically reviewing the results
- with clear rules for risks such as hallucinations, bias and data protection
AI does not replace judgement – it sharpens it
AI supports, but does not replace, professional judgement. The experienced tester remains the control instance, and responsibility for quality stays with people. This balance is what separates professional AI testing from blind trust in automation.
Frequently asked questions
What is AI testing?
AI testing is the systematic testing of AI systems for correctness, robustness, fairness and traceability. Because AI does not always answer the same way, it requires its own methods.
What is the difference between AI testing and testing with AI?
In AI testing, the AI is the system under test. In testing with AI, it is a tool that generates test cases or test data, for example. We cover both.
What role does the EU AI Act play?
The EU AI Act sets requirements for the quality, documentation and risk management of AI systems. Structured testing provides the evidence for this.
What qualifications do you have?
We are certified in A4Q AI Foundation and A4Q AI Essentials and work according to ISTQB principles.
