Collective Reflection on Conversational Generative AI for (Model-Based) Systems Engineering: Insights from the INCOSE French Chapter

Abstract

This paper provides a structured synthesis of a collective reflection on the motivations, potential benefits, current state, challenges, and future perspectives of using Conversational Generative AI (CG-AI) in the context of (Model-Based) Systems Engineering. Drawing on insights from a series of participatory workshops conducted within the CG-AI4IS working group of the INCOSE French Chapter, we summarise discussions among researchers, practitioners, consultants, and educators. Rather than presenting new empirical results, this work consolidates diverse viewpoints to: (1) identify the needs and expectations driving the adoption of CG-AI tools in systems engineering practice and education; (2) highlight current practices alongside the difficulties, limitations, and concerns raised by the community; (3) discuss emerging good practices for effective human-AI teaming; and (4) propose directions for future research, training, and governance to support the integration of CG-AI in (Model-Based) Systems Engineering.

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