AI and Systems Engineering: A Decade of Progress and Gaps.

H. Sinan Bank, Daniel R. Herber, Thomas Bradley· June 19, 2026 View original

Summary

This article reviews the evolution of AI and Systems Engineering (SE) over the past decade, identifying three phases of progress and critical research gaps. It also presents a human-AI agreement literature review to assess the relevance of publications and guide practitioners in AI adoption within SE.

The intersection of Artificial Intelligence (AI) and Systems Engineering (SE) has seen significant growth, particularly since a landmark INCOSE INSIGHT special issue in 2020. This paper provides a retrospective and prospective analysis of this evolving field, categorizing its development into three distinct phases: foundational, applied, and the current LLM inflection point. The authors articulate areas where the community has reached consensus and highlight persistent critical gaps in research. To complement this historical review, a comprehensive literature review was conducted, leveraging both human expertise and six AI models to evaluate the relevance of over 2,600 articles from INCOSE INSIGHT and SERC publications. The findings from this review pinpoint five crucial research gaps that need addressing. Furthermore, the paper offers practical guidance for professionals navigating the adoption, assurance, and workforce transformation challenges posed by AI in Systems Engineering. An accompanying web application, the AI4SE/SE4AI Explorer, is provided for readers to compare their own relevance judgments with those of human and AI raters.

Why it matters

This review provides a valuable roadmap for professionals in Systems Engineering and AI, offering insights into past developments, current trends, and future research directions. It helps practitioners understand where to focus their efforts for successful AI integration and addresses critical challenges in assurance and workforce adaptation.

How to implement this in your domain

  1. 1Review the identified research gaps to inform strategic planning for AI integration in SE projects.
  2. 2Utilize the AI4SE/SE4AI Explorer web application to assess the relevance of publications for specific needs.
  3. 3Develop training programs to upskill the workforce in AI and SE integration.
  4. 4Establish clear guidelines and frameworks for AI assurance in systems engineering contexts.
  5. 5Engage with the research community to contribute to addressing the identified critical gaps.

Who benefits

Systems EngineeringAerospaceDefenseAutomotiveSoftware Development

Key takeaways

  • The AI and Systems Engineering field has evolved through foundational, applied, and LLM inflection phases.
  • Critical research gaps remain in the integration of AI into Systems Engineering.
  • A human-AI literature review identifies key areas for future focus.
  • Practitioners need guidance on AI adoption, assurance, and workforce transformation in SE.

Original post by H. Sinan Bank, Daniel R. Herber, Thomas Bradley

"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 worksho…"

View on X

Originally posted by H. Sinan Bank, Daniel R. Herber, Thomas Bradley on X · view source

Want to go deeper?

Turn these trends into skills with Learnijoy's hands-on AI & tech courses.

Explore courses