This research presents an artificial intelligence-based framework to automate the preparation of progress payment certificates in construction projects, aiming to enhance efficiency, accuracy, and transparency in project management while minimizing financial delays. The preparation of progress payment certificates, which serves as the basis for contractor payments and work progress evaluation, frequently faces challenges such as time-intensive processes, human errors, and disputes among stakeholders. For instance, payment delays can disrupt cash flow, potentially stalling projects. The proposed framework employs machine learning to analyze project progress data from sources like Building Information Models (BIM) and IoT sensors. Additionally, natural language processing (NLP) is utilized to extract pertinent information from textual documents, including contracts, daily reports, and project specifications, to automate certificate preparation.

The study details the framework’s step-by-step workflow and evaluates associated challenges, encompassing technical issues (e.g., data integration), legal concerns (e.g., privacy compliance), ethical risks (e.g., algorithmic bias), and implementation hurdles (e.g., initial investment costs). Results indicate that this system significantly reduces processing time, minimizes errors, enhances cash flow, and mitigates disputes through transparent documentation. Automating progress payment certificates with AI represents a transformative solution for the construction industry. Despite challenges, its substantial benefits position it as a potential new standard. Future research should focus on testing the framework in real-world projects to validate its scalability, adaptability, and effectiveness across diverse construction contexts and regulatory frameworks, ensuring its practical viability.