The July 2026 Tech Talk was presented by Will Walker
Abstract
Model-Based Systems Engineering has spent a decade fighting the same battles: knowledge trapped in documents, modeling done by hand from a blank page, context siloed across a dozen tools, and a dependence on scarce experts. Artificial intelligence is now reshaping every one of those fronts and faster than most teams realize.
This talk is a grounded tour of how AI is genuinely impacting MBSE today, drawn from real, presented case studies by Ford, Dassault Systèmes, Capgemini, Quest Defense, and others. We’ll walk through six concrete impact areas: AI generating valid SysML v2 models from a single prompt; AI extracting formal, queryable models from legacy sketches and documents; automated failure and safety analysis (DFMEA) with reported 60–80% effort reductions; and of particular interest to a software audience, treating models like code, with CI/CD pipelines, the Model Context Protocol (MCP), and agentic “sense–decide–act” workflows driving the modeling tools themselves.
Just as importantly, we’ll separate signal from hype. The teams succeeding with AI all do the same unglamorous things first: they standardize with style guides and reuse libraries, and they keep a human in the verification loop. Attendees will leave with a clear mental map of where AI fits in MBSE, an honest view of the risks, hallucination, skill atrophy, IP exposure, and vendor over-promising — and a practical, five-step roadmap for adopting AI in their own practice starting Monday.
Key takeaways:
- The center of gravity for AI in MBSE is generation and extraction, turning prompts, sketches, and legacy documents into valid, connected models.
- Standardize before you automate: style guides and reuse libraries are what make AI output trustworthy.
- Treat models like code, CI/CD and MCP turn one-off generation into continuous, agent-driven workflows.
- AI augments engineering judgment; it doesn’t replace it, human verification is non-negotiable.
About the Presenter
Will Walker is the founder of CameoMagic, where he helps organizations adopt Model-Based Systems Engineering (MBSE), SysML, Digital Engineering, and AI-enabled engineering practices. Through consulting, training, and online educational content, he works with engineers across government and industry to improve system development workflows and model-based practices. As the creator of the CameoMagic YouTube Channel, he regularly shares tutorials, demonstrations, and insights on Cameo/CATIA Magic, SysML, AI agents, automation, and the future of digital engineering.
