Artificial Intelligence for Proactive Scheduling and Risk Prediction - Bhavinbhai G. Lakhani (The Bioscan, 2026)
Construction projects face persistent delay problems, which turn out to be costly. Proper scheduling and early risk prediction facilities act as a major help in solving the project’s issues. In healthcare infrastructures, work gets more difficult, as work is continued around live clinical operations. Traditional methods of scheduling often fail while anticipating project duration variability, regulatory timelines, equipment integration, and while anticipating trade coordination. Due to late risk identification, the average completion time of the project increases by 20–60% [1]. This paper presents practical data gathered by applying artificial intelligence (AI) forecasting tools on the Boston Children’s Hospital Hale Family Building project. This hospital project was completed in June 2022 by Suffolk Construction [2]. This paper helps to demonstrate how AI helps in project scheduling. Fixed, single-point estimates are turned into dynamic, probability-based plans, and a risk prediction facility is also provided by AI, months ahead of potential problems arising. All this is done with the help of project documentation review and a purpose-built experimental simulation. In our key findings, we found an 18% reduction in expected duration. Finally, learnings are included, so that any construction team can learn and begin using these techniques today. Data is presented using ten tables and three diagrams for better understanding.