Conceptual Cost Estimating AI

Conceptual cost estimating produces budget-level cost projections from early design parameters — building type, gross area, number of floors, construction type, quality level, and location. These early estimates set expectations with owners and guide major design decisions, making their accuracy critically important even though little design information is available.

AI conceptual estimating analyzes cost data from completed projects of similar type, size, and location to produce more reliable early estimates than traditional parametric methods. Instead of applying a single cost-per-square-foot factor, AI considers the specific characteristics of the proposed building — the structural system, the facade complexity, the MEP intensity, the site conditions — and adjusts the estimate based on how these factors affected costs on comparable completed projects.

The confidence range is as important as the point estimate. AI provides a probable cost range that reflects the uncertainty inherent in early estimates, along with the key cost drivers that the design team can influence. This shifts the conversation from "the building costs $50 million" to "the probable cost range is $45-55 million, with facade selection being the single largest variable." This framing helps owners make informed decisions about where to invest and where to economize.