Test-driven AI development is particularly at home in the areas of artificial intelligence, automation and Industry 4.0. It describes an approach to the development of applications with artificial intelligence (AI) in which specific tests are first written for a desired function before the actual AI code is developed.
This means that developers first consider how an AI should behave in a certain situation. This desired behaviour is recorded in the form of tests. Only then is the AI programmed to pass these tests. This ensures, step by step, that the AI does exactly what it is supposed to do.
An illustrative example: In a factory, an AI is supposed to recognise faulty products on an assembly line. First, the team defines test cases - such as images of good and bad products. The AI is only considered ready for use when it reliably and correctly assigns these examples.
Test-driven AI development therefore ensures better control, more security and fewer errors when introducing new AI systems. Companies benefit because risks are minimised and the quality of AI applications increases.















