Abstract

The integration of artificial intelligence (AI) into construction projects across the Middle East, particularly in Gulf Cooperation Council (GCC) countries, presents unprecedented opportunities for enhanced project delivery, predictive analytics, and digital transformation. However, the success of AI-driven construction initiatives fundamentally depends on robust data governance frameworks and high-quality data ecosystems. This comprehensive review examines the intersection of data governance, data quality management, and AI deployment in Middle East construction, with specific focus on the United Arab Emirates (UAE), Saudi Arabia, Qatar, and Oman. Through systematic analysis of 91 scholarly sources and regional case studies including NEOM, Dubai Roads and Transport Authority (RTA), and Building Information Modeling (BIM) adoption initiatives, this article identifies critical success factors, persistent challenges, and emerging frameworks that shape AI-enabled construction outcomes. Key findings reveal that technology and infrastructure factors most strongly influence AI success, followed by governance and human enablers, with data quality and scalable infrastructure serving as critical mediators. The article synthesizes evidence on prominent governance frameworks including the Cognitive Project Management AI (CPMAI) model, AI-driven data mesh architectures, DAMA-DMBOK AI-assisted governance, and regional regulatory instruments from the Saudi Data and Artificial Intelligence Authority (SDAIA) and Dubai Government Accelerators (DGA). Persistent challenges include fragmented and non-standardized data across project phases, ownership and intellectual property ambiguities on collaborative platforms, data scarcity for supervised learning models, and insufficient lifecycle governance mechanisms. The article proposes evidence-based policy recommendations including mandated lifecycle data-quality metrics in public procurement, adoption of domain data contracts and mesh patterns, promotion of automated governance tooling, strengthened workforce training programs, and clear sovereignty and residency rules for cross-border projects. This research contributes to the emerging body of knowledge on trustworthy AI in construction by providing a comprehensive framework that integrates technical,organizational, and regulatory dimensions of data governance tailored to the unique socio-technical context of Middle East construction ecosystems.