AI and Construction Project Schedules Efficiency: A Review
DOI:
https://doi.org/10.38124/ijsrmt.v4i6.761Keywords:
Artificial Intelligence, Construction Scheduling, Project Managemen, Machine Learning, BIM, Delay Prediction, Automation, ChatGPT, LLMsAbstract
The construction industry continues to grapple with problems relating to project delivery within the set timelines and budget due to consistent issues with project scheduling. In the recent past, the emergence of Artificial Intelligence (AI) has presented opportunities to transform the planning and execution of construction schedules. This review looks at the efficiency of construction project schedules due to the impact of AI technologies, analyzing peer-reviewed studies, industry reports, and case studies published between 2000 and 2023. The study incorporates key AI methodologies such as machine learning, deep learning, automated planning and scheduling systems, and language models, including ChatGPT, to assess their impact on delay prediction, resource optimization, and schedule automation effectiveness.
The research outcomes show AI-enabled systems enhance schedule precision, adaptability, and making better decisions when utilizing past data, real-time data, and integrating with Building Information Modeling (BIM). With appropriate structured data, several AI applications have been proven to enhance critical path delay identification and reduce planning time by as much as 30% for construction schedule optimization. Fragmented data, high cost of initial investment, low AI literacy among the professionals, and ethical issues are still barriers to applications of AI. The review concludes that AI, while not a replacement for human expertise, can serve as a vital augmentation tool in construction scheduling when applied responsibly and strategically. The paper offers targeted recommendations for construction firms, policymakers, and researchers to facilitate AI integration and foster sustainable digital transformation in the built environment.
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Copyright (c) 2025 International Journal of Scientific Research and Modern Technology

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