Artificial Intelligence for Proactive Scheduling and Risk Prediction

Abstract

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.