Where AI is genuinely being used across engineering disciplines today — computer vision for structural inspection, natural-language CAD/BIM interfaces, AI code generation for engineering scripts, domain-specific electrical applications, and the honest caveat every one of them shares.
This module grounds everything the program has covered so far in what practicing engineers are actually using in production right now: vision models flagging cracks, corrosion, and weld defects in structural inspection imagery, natural-language interfaces querying and generating design intent inside CAD and BIM software, and code-generation copilots writing the Python scripts behind load calculations, unit conversions, and report generation. It then walks through a concentrated cluster of electrical-engineering applications this studio has published a dedicated article on — NEC load calculations, protection coordination and relay settings, PV and energy storage sizing, and arc flash analysis.
By the end of this module you should be able to explain why every one of these applications still requires the same professional verification any engineering calculation would — a licensed engineer's review, not blind trust in AI output — and how Module 6's prompt engineering and Module 9's RAG are the techniques actually running underneath most of them. This module also previews Project 5 (AI-Powered Engineering Defect Detection Pipeline), one of the five real-project case studies in the Module 18 slot.