
arXiv:2606.19630v1 Announce Type: new Abstract: The March 2020 INCOSE INSIGHT special issue on AI and Systems Engineering (SE) became the most downloaded issue in the publication's history and launched a research community that now draws over 250 registrants to its annual workshop. In this article, we trace the progress in AI and SE across three phases (labeled here foundational, applied, and LLM inflection) based on the authors' reading of the field's core papers, and describe our opinions of where the community has converged and where critical gaps remain. Separately, a human-AI agreement li
This paper reflects on progress in AI and Systems Engineering (SE) over the past decade, culminating in the significant impact of Large Language Models (LLMs), indicating a mature stage of reflection and future planning for the field.
The deep integration of AI into Systems Engineering (AI4SE) signifies a critical evolution in how complex systems are designed and managed, impacting efficiency and capabilities across all sectors reliant on robust engineering.
The explicit recognition of an 'LLM inflection' within AI and SE suggests a new paradigm for how AI tools will be developed and applied in practical engineering challenges, accelerating automation and potentially reducing human error.
- · AI software developers
- · Systems engineering firms
- · Academia focused on AI4SE
- · Industries with complex engineering (e.g., aerospace, defence)
- · Traditional SE methodologies without AI integration
- · Companies slow to adopt AI-driven SE tools
The adoption of AI in Systems Engineering will streamline design processes and improve the reliability of complex systems.
This efficiency gain could lead to faster product development cycles and lower costs for technologically advanced goods.
Entire industries could undergo significant restructuring as AI-driven SE allows for previously unfeasible levels of complexity and automation, shifting competitive landscapes.
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Read at arXiv cs.AI