AI-based algorithms offer the opportunity to develop robust sensor systems that generate valid and safe operations in a wide range of environmental conditions. The generation of reproducible test scenarios under different environmental conditions is essential for development of these systems. Therefore, an outdoor test environment is being build up in AI-Test-Field. The aim is to carry out autonomous long-term tests to generate sensor data under variable field, weather and plant conditions. In addition to the sensor signals, meta-data will be recorded for the development and evaluation of AI methods. The project includes the use of different sensor systems (laser scanner, stereo cameras, ToF camera, ultrasonic and radar) as well as the exemplary transfer to real machines for different use cases (row cropping, grassland and bare ground). The contents of AI-Test-Field form an essential basis for the certification of such sensor systems for autonomous field robotics.