In Architecture, Engineering, and Construction, the value of our work isn’t just in the drawings, models, or reports—it’s in the data behind them.
And here’s the kicker: as AI continues to mature, it’s only going to be as smart as the data we give it. Garbage in, garbage out—just with fancier math.
That’s why a strong Common Data Environment (CDE) isn’t optional anymore. It’s the foundation for everything we want to do with AI.
Let’s be honest—how many times have you heard these questions on a project?
- “Where’s the latest model?”
- “Do we have the latest program update?”
- “Wait, which set of specs are we looking at?”
- “Whose meeting notes are these?”
- Whats this final.final..v3 file?
If your data is scattered, duplicated, or outdated, AI isn’t going to magically fix it. In fact, it’ll just automate the chaos faster.
But with a well-structured CDE, AI becomes a game-changer:
– Automating repetitive tasks nobody actually likes doing.
– Surfacing design risks before they become change orders
– Connecting insights across disciplines (without 47 reply-all emails)
Supporting better decisions, faster
The real opportunity isn’t about replacing expertise—it’s about amplifying it. Get your data in order today, and when AI takes on a bigger role tomorrow, it’ll be working for you—not against you.
Because in the end, the firms that treat their data like an asset—not a scavenger hunt—are the ones who will thrive
Wired with April Kane: Exploring Revit Electrical 