DIGITAL TECHNOLOGIES IN CONSTRUCTION PROJECT MANAGEMENT

Abstract

The construction industry represents one of the most complex and risk-intensive sectors of the global economy, significantly contributing to national Gross Domestic Product (GDP) while simultaneously facing persistent challenges such as budget overruns, schedule delays, low productivity, and fragmented decision-making processes. Large-scale and megaprojects, in particular, frequently exceed their initial budgets and timelines due to inaccurate cost estimation, insufficient planning, unclear project scopes, and the predominance of experience-based rather than data-driven managerial decisions. In this context, digital transformation has emerged not merely as an innovation trend but as a strategic necessity for improving efficiency, transparency, and risk management in construction project management. This study investigates the role and impact of four major digital technologies—Building Information Modeling (BIM), the Internet of Things (IoT), Artificial Intelligence (AI), and Digital Twin systems—within the lifecycle of construction projects. The research adopts a comprehensive analytical and literature-based approach, examining recent academic studies, industry reports, and global case examples to evaluate the effectiveness, implementation levels, and strategic contributions of these technologies. The findings indicate that BIM significantly enhances interdisciplinary coordination, conflict detection, visualization, sustainability analysis, and cost-time management, with the highest impact observed during early project phases where cost influence potential is greatest. IoT technologies contribute to real-time monitoring of safety conditions, environmental parameters, equipment performance, and resource utilization, thereby improving operational control and reducing on-site risks. Artificial Intelligence enables advanced data analytics, predictive modeling, and decision-support mechanisms, particularly when integrated with BIM and IoT platforms, although its adoption in construction remains comparatively limited due to data standardization and organizational barriers. Digital Twin systems extend beyond static modeling by establishing real-time synchronization between physical assets and digital replicas, allowing continuous lifecycle optimization and performance monitoring. The study concludes that the integrated application of BIM, IoT, AI, and Digital Twin technologies forms a synergistic digital ecosystem capable of transforming construction project management into a data-driven, predictive, and strategically optimized discipline. Despite existing challenges such as traditional management culture, fragmented data structures, and resistance to change, the adoption of digital technologies is essential for reducing project risks, improving productivity, and enhancing global competitiveness in the construction industry.