AI for AEC

The AEC industry sits on massive volumes of unstructured data — drawings, specs, submittals, RFIs, contracts, field reports — most of it locked in PDFs and file shares. General-purpose AI tools like ChatGPT can write a nice email, but they fall apart when you ask them to find the fire-rating requirement for a specific wall assembly in a 400-page spec. That is the gap AI for AEC fills.

Domain-specific AI for AEC is trained to understand construction terminology, drawing conventions, and the relationships between documents. When a project engineer asks "what waterproofing system was specified for the below-grade walls?", the AI doesn't just keyword-match — it understands that the answer lives in the specifications (probably Division 07), pulls the relevant section, and cites exactly where it found the information. That citation piece is critical. In construction, an answer without a source is just a guess.

The practical starting point for most firms is search: connecting the AI to your existing document management system (SharePoint, Egnyte, Procore, etc.) and letting teams ask questions in plain language instead of hunting through folder structures. From there, firms layer on compliance checking, drawing review, and submittal processing — each one automating hours of manual work per project.