AI-Agent Application for Semantic Data Enrichment in Ventilation Systems Using National Nomenclature for IFC and GS1-Based Product Information

Abstract

This study investigates the potential of AI agent systems to automate information management within the mechanical, electrical, and plumbing (MEP) construction process. Currently, building information model (BIM) data is often exchanged manually via 2D drawings and Excel spreadsheets, leading to significant discontinuities in information flow across the design, procurement, and construction phases. Based on a systematic identification of these discontinuities, a simulation was developed to evaluate the feasibility of AI agent-based automation. The results demonstrate that AI agents can effectively enrich and transform a machine-readable engineering bill of materials (E-BOM) into a structured manufacturing bill of materials (M-BOM). Owing to the standardized structure of Finnish MEP data, the solution is not limited to a single case but can be generalized across different MEP domains, enabling broader automation of data flows. These findings suggest that AI agents offer substantial potential as next-generation solutions for automating information workflows in construction.