Test-driven AI development is particularly at home in the areas of Artificial Intelligence, Automation, and Industry 4.0. It describes an approach to developing applications with Artificial Intelligence (AI) where concrete tests for a desired function are written first, before the actual AI code is developed.
This means: Developers first consider how an AI should behave in a specific situation. This desired behaviour is documented 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.
A clear example: In a factory, an AI is to be used to detect faulty products on a conveyor belt. First, the team defines test cases – for instance, pictures of good and bad products. The AI is only considered ready for deployment once it reliably assigns these examples correctly.
Test-driven AI development thus ensures better control, increased security, and fewer errors when introducing new AI systems. Companies benefit because risks are minimised and the quality of AI applications rises.
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