The article examines the impact of structural steel detailing accuracy on the formation and evolution of errors along the KM–structural steel–fabrication–erection chain under compressed construction schedules. The aim of the study is to demonstrate how the degree of formalization of geometry, tolerances, specifications, and marking transforms an information model from a set of drawings into an instrument for managing the risks of defects, downtime, and re-approvals. The relevance of the work is driven by the growing share of BIM-oriented projects, the integration with robotic fabrication, and kit-based logistics, under which any geometric uncertainty is rapidly translated into financial and time losses. Based on an analysis of publications and industry case studies, structural steel accuracy is interpreted as a multicomponent, operationally verifiable parameter that includes member and joint geometry, the structure of tolerances, semantically enriched specifications, and robust marking. The scientific novelty lies in the systematization of errors into three interrelated groups (geometry and holes, information losses, erection and coordination failures) and in linking these groups to specific choices in detailing, modeling standards, automated control, and zone-based logistics. It is shown that improving the accuracy of structural steel reduces the share of defects by shifting control into the computational domain, establishing a closed model–fabrication–erection loop, and relying on verifiability and consequence criteria when selecting the level of detail, especially in congested zones and critical joints. It is concluded that the balance between model elaboration and labor input determines the actual payback of accuracy, and that stable quality growth is achievable only in the presence of standards, a library of typical joints, regulated checks, and a controlled change-management workflow. The article is intended for structural engineers, BIM coordinators, specialists in the fabrication and erection of steel structures, project managers, and researchers in digital construction.