The Architecture, Engineering, Construction, and Operations (AECO) industry stands at a pivotal crossroads of digital transformation. While Building Information Modeling (BIM) has fundamentally reshaped design, construction, and facility management practices over the past two decades, the emergence of advanced technologies—including Artificial Intelligence (AI), Digital Twins (DT), Blockchain (BC), the Internet of Things (IoT), and advanced automation signals a new era of possibilities that extend well beyond BIM's original capabilities. This Special Issue, Beyond BIM: Navigating the Transformative Journey of the AECO Industry, was conceived to provide a platform for researchers worldwide to explore these technological frontiers and their integration with established BIM processes. The response from the academic community was overwhelming, with numerous high-quality submissions received from researchers across multiple continents. Following rigorous peer review, fourteen papers were selected for publication, collectively representing contributions from institutions in Australia, the United Kingdom, Taiwan, Hong Kong, South Korea, New Zealand, Malaysia, Iran, Nigeria, South Africa, the United States, and China.
The papers assembled in this Special Issue converge on several interconnected themes that illuminate the trajectory of digital innovation in the AECO sector. A dominant theme is the pursuit of semantic interoperability and cross-domain integration. The persistent challenge of data fragmentation across disconnected systems, including BIM models, IoT sensors, computerized maintenance management systems, and manufacturer specifications, continues to impede operational efficiency. Hosseini et al. (2026) address this challenge by developing a unified ontology framework that integrates BIM, IoT, and maintenance service data into a machine-interpretable knowledge infrastructure, demonstrating significant efficiency gains over manual information retrieval. This semantic approach to data integration represents a critical step toward intelligent facility management systems capable of automated reasoning and decision support.
The integration of Digital Twin technology with BIM emerges as another significant research stream. Rashidi et al. (2026) provide a comprehensive scientometric and systematic review revealing that over 90% of BIM-DT publications have appeared since 2020, with research clusters spanning Construction 4.0 technologies, smart cities, heritage BIM, facility management, and energy sustainability. The operation phase of building lifecycles has attracted particular attention, reflecting industry demands for real-time monitoring and predictive capabilities. Complementing this perspective, Omrany et al. (2026) examine DT applications for education, training, and learning in construction, proposing a conceptual framework that integrates digital literacy and workforce development as essential factors for sustainable technology adoption. Ebiloma et al. (2026) extend this discourse to developing economies, identifying key drivers for Digital Twin maintenance management in Nigerian healthcare facilities, with enhanced traceability of building failures emerging as the most influential factor.
Blockchain technology's potential for ensuring data integrity and enabling trustworthy collaboration is explored in two complementary studies. Adu-Amankwa and Rahimian (2026) investigate practitioners' perspectives on BC-enabled DT for building commissioning, revealing perceived benefits in real-time monitoring, enhanced data access, and bolstered security. Kim et al. (2026) present a BC-enhanced computer vision framework for remote safety inspection, integrating smart contracts to manage inspection workflows and ensure immutable recording of hazard detection results. These studies collectively demonstrate blockchain's capacity to address longstanding trust and verification challenges in construction processes.
Automation through AI and machine learning constitutes another thematic cluster. Pal et al. (2026) introduce an innovative approach to automated schedule updating by synchronizing project schedules with reality models through Natural Language Processing and computer vision, extracting Location-Element-Material information without relying on labor-intensive 4D BIM models. Cai et al. (2026) propose a framework combining Scan-to-BIM with generative design for interior reconstruction, leveraging deep learning for semantic segmentation. Similarly, Amarkhil et al. (2026) illustrate the potential of computational optimization in project planning by integrating BIM, advanced planning and scheduling, and constraint programming for automated construction scheduling. In the same vein, Moghaddam et al. (2026) present a practical BIM and Augmented Reality framework for facility maintenance management, which incorporates a novel Visual-Inertial Simultaneous Localization and Mapping method that removes the need for preliminary site scanning.
The human dimension of digital transformation receives critical attention in several contributions. Bidhendi et al. (2026) developed a human-centric change management framework for BIM implementation, identifying training, organizational competency assessment, and resource allocation as pivotal activities for successful adoption. This finding resonates with Perera et al’s (2026) investigation of Construction 4.0 technology adoption in Australian firms, which categorizes technologies into real-time data capture, digital communication, data analysis, visualization, and off-site construction applications. Abolghasemi et al. (2026) examine stakeholder management dynamics in Malaysian residential projects, confirming that effective stakeholder management enhances satisfaction and consequently improves project performance. The study by Soltanmohammadlou et al. (2026) apply fuzzy DEMATEL methodology to model safety risk factors in earthmoving equipment operations on Australian construction sites, revealing construction site management and workforce factors as central determinants within the safety system.
Collectively, these fourteen articles underscore that the journey beyond BIM requires not merely technological sophistication but also attention to semantic integration, organizational readiness, and human-centric implementation strategies (Oraee et al., 2026). The research reveals a productive tension between comprehensive data models that prioritize precision and practical solutions that emphasize accessibility and usability. Future research should prioritize empirical validation of proposed frameworks, scalability across diverse building systems and geographic contexts, cybersecurity considerations for increasingly connected built environments, and the development of standardized approaches to facilitate industry-wide adoption.
We extend our sincere gratitude to Professor Chimay J. Anumba, Editor-in-Chief, for his support in bringing this Special Issue to fruition. We also thank the authors for their valuable contributions and the reviewers for their rigorous and constructive feedback. We trust that readers will find this collection informative and inspiring as the AECO industry continues its transformative digital journey.
