Digitalization in construction is transforming construction by converting actual site data into computable assets. The core of this transition is in the automated reconstruction of a Building Information Modeling (BIM) model from point clouds, converting raw scan data into traceable, analysis-ready as-built models. This study presents a rigorous scan-to-BIM workflow for steel structural frames that emphasizes automation and metric-based validation. High-density point cloud data were obtained using Faro Focus Laser Scanner 3D X130; registration and processing in Autodesk Recap Pro were maintained with quality metrics threshold (overlap > 60%, balance > 20%, and points < 6 mm > 99.7%) to ensure a chain of evidence; segmentation to isolate the elements, followed by semi-automated reconstruction in Autodesk Revit. A sample steel structural frame in a laboratory environment demonstrated that the workflow deliverables were appropriate for future investigations, such as for as-built structural performance, quality control, and asset maintenance. The contribution of this study is an automation-ready, reproducible workflow that connects data acquisition using a 3D laser scanner with accuracy assessment for a future analysis-ready BIM model. The workflow enhances the existing knowledge in scan-to-BIM research by providing a validated reference for academic and industry applications, hence supporting the digital transformation goals of Malaysia’s Construction 4.0 Strategic Plan 2021–2025.