The construction industry in Uzbekistan, like many others worldwide, faces significant challenges in document management and compliance with the vast and complex regulatory environment, notably "Construction Norms and Regulations" (CNR) and "State Standard of the Republic of Uzbekistan" (SSU) standards. This research aims to develop and evaluate an artificial intelligence (AI)-powered system specifically designed to automate the review of construction documents within the Uzbek context. Utilizing a combination of natural language processing (NLP) and machine learning (ML) techniques, the proposed system aims to significantly reduce the manual effort and time required for document review processes while improving accuracy and compliance rates. Our methodology encompasses the collection and annotation of a substantial corpus of construction documents, the development of an AI model trained on this dataset, and a rigorous evaluation of the system's performance against manually reviewed benchmarks. Results indicate a substantial improvement in both efficiency and accuracy of document review processes, with the AI system achieving 95% accuracy in compliance detection compared to 81% for traditional manual methods, and reducing review time from over 30 hours to under 4 hours per document set. The system demonstrated precision of 0.89, recall of 0.95, and an F1-score of 0.95 across diverse case studies in Tashkent, Samarkand, and Bukhara. The contributions of this study are twofold: first, it provides a novel application of AI technologies for automating document review processes in the construction industry of Uzbekistan, addressing specific regulatory requirements; second, it contributes to the broader field of construction informatics by demonstrating the potential of AI and ML technologies in enhancing regulatory compliance and efficiency. This research lays the groundwork for further exploration into AI-powered document management systems and their potential to transform the construction industry's approach to regulatory compliance and project management.