AI is increasingly used for systems and companies are integrating Machine Learning methods as well as Generative AI into modern products. For Systems Engineering this leads to new challenges, for example due to the increasing importance of data quality, data privacy or new legislation. This article highlights key challenges arising from the integration of AI components into technical systems and discusses the impact on classical role models for Systems Engineering. The paper presents results from a literature review as well as a view on how the development of AI-based systems is transforming traditional Systems Engineering from perspective of design teams. New demands on data quality assurance and legal risk management as well as establishing new roles in Systems Engineering are discussed. In addition, theses for shaping the future of Systems Engineering are presented.
