Realizing the Potential of AI in Construction Delay Analysis: An Examination of the Issues and Improvement Needs in Delay Analysis Techniques at SMDC Projects

This research investigates the potential of Artificial Intelligence (AI) to improve delay analysis techniques within the construction industry, specifically focusing on SM Development Corporation (SMDC) projects. The study aims to identify the limitations of traditional delay analysis methods (Balli & Güven, 2022) and explore how AI can address these shortcomings to enhance project outcomes (Egwim et al., 2021). This likewise explores the question: how can SMDC project teams use artificial intelligence to prevent delays? This study explores three crucial aspects of project team members' work—documentation, analysis, and comprehension of delay analysis and AI potentials—by considering common delay causes, the challenges faced by project teams, and insights from delay analysis, scheduling tools, and AI tools as discussed in the literature. The research employs a mixed-methods approach. A comprehensive literature review examines existing delay analysis techniques and the application of AI in construction (Ivanović et al., 2022). Survey regarding the understanding and insight of SMDC project team members regarding delay analysis and the potential of AI Tool for delay analysis was conducted. Further, interview to project team members of SMDC projects was conducted to assess current delay analysis practices and identify areas for improvement (Boyacioglu et al., 2022). The study anticipates that AI-powered solutions can offer more objective, data-driven, and real-time delay analysis compared to traditional methods (Egwim et al., 2021). The research will likely reveal challenges in data quality, expertise, and integration that hinder AI implementation (Almén, 2024). The research is limited by the availability of high-quality data from SMDC projects and the potential for bias in case study selection (SANNI-ANIBIRE et al., 2020). The generalizability of findings may be restricted to similar construction companies and project types (Ivanović et al., 2022).