AI for takeoff and estimating: what the evidence actually says

AI takeoff and estimating tools are improving quickly, and the marketing claims are bold. Before you put AI output into a live bid, it is worth knowing what independent testing and experienced estimators actually report.

What independent testing found

A study from Utica University compared an AI takeoff tool with a contractor’s own takeoff on a live commercial project. Counts were close to exact, but area-based quantities were consistently underestimated, and accuracy dropped on irregular geometry and complex façades. The authors concluded that estimator oversight remains essential.

Where AI struggles

• Low-quality scans and missing pages: it cannot count what it cannot read
• Unusual symbols and irregular shapes
• Scope decisions: what belongs in your price is still the estimator’s call

Where it genuinely helps

• Reading and structuring long tender packs and BOQs
• Counts and first-pass quantities that a person then checks
• Cross-checking a takeoff that has already been done
• Putting supplier quotations into a like-for-like comparison

How we apply this at Monjez

We treat AI output as a first draft. Every workflow links its outputs to their sources, flags what it is unsure about, and leaves quantities, rates and scope decisions with your estimator. We test on your own documents before go-live and tell you what we find.