In this presentation, the author uses practical examples to show how AI induced digital automation can be achieved in a variety of applications and methods in NDT. The focus is on which foundations companies and users have to create in order to introduce AI in digital x-ray, visual testing technology and beyond and which potentials lie therein. It highlights the interaction of different data processing (archiving, NDT management, mobile applications and evaluation software) systems and their correspondence for the optimal use for AI technology. The talk will focus on different setups of systems highlighting advantages and disadvantages for the future use of AI. It also defines data structures and formats that are prerequisite for AI training and usage. Using various project examples from the areas of RT weld inspection, on-stream analysis, visual testing and others, the author shows real-world application examples. These examples reflect on the technological development, the implementation and business relevance for the respective partner companies and therefore paints a holistic picture of the industrial use of AI. This way the talk will describe how business cases for AI look like in NDT. The presentation reflects on the experience gained in these specific projects and provides recommendations for action as well as the prerequisites to lead users into a digitally automated future. It addresses the hurdles of AI implementation in NDT processes, highlighting in particular the training process, the continuous adaptation of AI systems, and the current hurdles of qualification of corresponding systems. Also, the presentation shows latest research results from the field of human – AI interaction in the field of NDT.