supplier is ending production. Pro - vide a list of all components this system interfaces with, identify in - terface standards, and performance specs. Query authorized warfight - ing supply catalogs for replacement components that match the interface, physical space, and performance re - quirements. The new SysML v2 paradigm, com - bined with AI agents, lowers the com - plexity barrier to accessing data and makes authoritative data available to the entire workforce, on demand, in their own words. This completely bypasses the complexity of learning new tools in order to access the data. A program manager who routinely asks an AI agent to summarize a con - tract modification will find it entirely natural to ask an AI agent about the system model. The interface is iden - tical, and the cognitive leap is small. As the workforce adopts new ways of doing business with AI, the concept of using an AI agent to query and in - vestigate the system model is just an - other tool in the AI Swiss Army knife. AI agents can also be leveraged to generate AI-assisted models from initial program requirements and documents. Research presented at the 2024 INCOSE International Sym - posium demonstrated that AI agents can translate natural language re - quirements into valid SysML v2 struc - tures, and benchmark studies show that this approach is rapidly matur - ing. These models must still be vetted and refined by expert Modelers; how - ever, even imperfect scaffolding can dramatically reduce the time required to develop a system model. A final vision of future capability is AI-assisted trade studies. A federa - tion of models coupled with AI agents opens the door to automated, sys - tem-wide trade studies to efficiently evaluate trade options and empower evidence-based decisions. This sup - ports the ATS imperative to deliver decisive capability to the warfighter. Ultimately, the proof of successful digital transformation will be evident when the cultural challenge is over -
come, as the workforce recognizes the ease of access and utility of these tools and seeks them out. The pre - vailing mood no longer will be “Why should we go digital?” but rather “I don’t want a static document, I want access to the model.” The Decision We Face The emergence of powerful AI tools, along with SysML v2, provides an opportunity we must take to scale digital engineering across the war- fighting acquisition enterprise. The ATS provides the imperative to adopt new systems engineering approaches and to incorporate AI into our work - flow. The workforce is already being trained to integrate AI into their daily workflows, and this direct connection will expand AI-assisted document generation and querying into AI-as - sisted model generation. Authorita - tive data will be available to the entire workforce on their own terms and in their own language.
To enable this vision, we must pre - pare now by laying the framework and governance for creating digital threads that connect enterprise data and governance for how AI will be used with modeling and responses vetted and used to make real acqui - sition decisions. KOZOLA is a professor at Warfighting Acqui- sition University, where he teaches systems engineering and digital acquisition. He holds BS and MS degrees in Mechanical Engineer- ing and is a certified Systems Engineering Project Management professional. His work focuses on helping the warfighting acqui- sition workforce apply digital engineering, model-based systems engineering, and artificial intelligence to improve acquisition decision-making. The author can be contacted at brian.kozola@waru.edu. The views expressed in this article are those of the author alone and not the Department of War. Reproduction or reposting of articles from Defense Acquisition magazine should credit the authors and the magazine.
SEPTEMBER –OCTOBER 2026 | DEFENSE ACQUISITION MAGAZINE 47
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