AUTOMATION OF CLOSEOUT AND PUNCHLIST WORKFLOWS USING DIGITIZED INTELLIGENCE SYSTEMS

Abstract

The management of punchlist items and the closeout phase of construction projects are crucial factors that determine the project's quality, compliance, and timely handover. Conventional closeout and punchlist processes are primarily manual, disjointed, and prone to mistakes, delays, and difficulties with stakeholder collaboration. This study investigates the use of digital intelligence technologies to automate closeout and punchlist procedures in order to overcome these constraints. The study suggests a conceptual automation framework that integrates artificial intelligence-based defect identification, automated punchlist generation, intelligent task assignment, real-time progress tracking, and centralized digital documentation using a hypothetical, mixed-methods research design. Based on organized stakeholder answers and simulated project data, the analysis is assessed using percentage frequency analysis and interpretive discussion. The results show that automation improves punchlist management accuracy and completeness, shortens closeout times, and increases stakeholder coordination and transparency. Notwithstanding its speculative nature, the study shows how digital intelligence systems might revolutionize closeout procedures and provide a strong basis for further empirical investigation and real-world application in building project management.