Industrial Challenges for AI Systems Engineering.

Abstract Integration of Artificial Intelligence (AI) methods into industrial systems engineering processes is challenging. Despite an increasing body of knowledge on AI techniques and impressive state-of-the-art reports, the application of AI in industrial contexts is only at an early stage. This paper summarizes challenges for AI Systems Engineering. Two examples of AI systems engineering are provided: the TRUMPF Sorting Guide and ABB BatchInsight. Summaries of the projects give insights into the project executions and related challenges. The learnings from these projects also show that increased maturity of AI systems engineering can be expected from increased method competence and adjusted project setups. Here guidelines and best practices for AI systems engineering can support.