AI In Construction, Build Smarter, Not Harder

Through supporting and working with construction firms in their efforts to adopt AI, we have learned it’s not as simple as it sounds.

Across the board, we are hearing some consistent challenges:

🧩 Data is still too fragmented. Project info lives in silos across departments and legacy systems, making it tough for AI to pull anything meaningful.

🏗️ Field and office teams often aren’t aligned. If the site crew and HQ are using different processes, no amount of AI can close that gap.

🧠 There’s a real talent gap, not just in the trades, but in people who understand both construction and data science.

⏱️ ROI expectations don’t always line up with project timelines. Many AI tools need time to learn and improve, but construction is all about short-term cycles.

🔧 And if AI tools don’t integrate well into existing workflows? They just don’t get used, no matter how powerful they are.

Interestingly, it's not always the biggest firms winning with AI. 

It’s the ones who are slowing down to get the fundamentals right before chasing the next shiny thing.