aspg-22-4356-1791483578 20261008181938 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group International Journal of BIM and Engineering Science IJBES 2571-1075 2026 12 2 Ann Wolter HAN University of Applied Sciences, Arnhem, The Netherlands Paul Bailey The School of Science, Engineering and Environment, University of Salford, Manchester, UK Raja Ahmed Hassan The School of Science, Engineering and Environment, University of Salford, Manchester, UK Wipitha Mazungwi The School of Science, Engineering and Environment, University of Salford, Manchester, UK This paper provides a comprehensive systematic review of Building Information Modeling (BIM) integration across ten engineering disciplines, synthesising publications from January 2020 to January 2026. It identifies convergent trends, persistent knowledge gaps, and translational barriers that separate research prototypes from scalable industry practice. A PRISMA-guided systematic review was conducted across Scopus, Web of Science, ASCE Library, and ScienceDirect. An initial corpus of 4,712 records was screened and quality-assessed, yielding 63 papers for quantitative synthesis and a broader qualitative corpus of 293 studies spanning ten sub-domains: BIM–digital twin integration, BIM and artificial intelligence/machine learning, interoperability and IFC, structural engineering, MEP and building services, facility management and operations, BIM–GIS for smart cities, off-site and modular construction, adoption barriers, and energy and sustainability analysis. Annual BIM publications grew by approximately 256% between 2019 and 2024. BIM–AI/ML and BIM–digital twin integration are the two fastest-growing sub-domains, yet both remain constrained by data standardisation deficiencies and a shortage of domain-specific training datasets. IFC-based interoperability has matured significantly, but real-time bidirectional exchange across disciplines remains nascent. Structural engineering applications exhibit the highest technology readiness, while BIM–GIS integration for smart-city applications shows the widest gap between published prototypes and commercial deployment. The review delivers a thematic roadmap and a consolidated evidence base for prioritizing investment in digital workflows, standards development, and workforce training. An original four-layer integrated framework is proposed that connects engineering code provisions, AI/ML analytics, digital twin synchronisation, and automated quantity extraction within a single traceable workflow. 2026 39 47 4356 https://creativecommons.org/licenses/by/4.0/ 10.54216/IJBES.120206 https://www.americaspg.com/journal/22/article/4356 https://www.americaspg.com/storage/articles/manuscripts/01KT6NVWGA584W1EZWNSB137SB.pdf