The purpose is to get an overview of current or planned development activities -starting from data engineering to model management and pipeline/workflow automation. As the operationalization of AI/ML prototypes (MLOps) often fails in practice, we analyze which techniques are already in use and which competencies can potentially be targeted to master complexity and traceability.