Methods for enhancing AI applications in improving schedule and resource management in agile infrastructure projects in Saudi Arabia

Abstract

The study aimed to investigate the extent to which artificial intelligence (AI) enhancement methods (big data analysis, scheduling automation, real-time monitoring, and predictive analytics) are utilized to improve schedule and resource management in agile infrastructure projects in Saudi Arabia. The study population consisted of employees working on agile infrastructure projects in the Kingdom. The sample included (95) individuals. The researcher employed a descriptive approach and used a questionnaire as the study tool. The study revealed several findings including that the use of AI enhancement methods received a high response rate, indicating their significant adoption in the field. The first method, big data analysis, had a mean score of (3.70), while the second method, scheduling automation, had a mean score of (4.05). The third method, real-time monitoring and predictive analytics had a mean score of (3.42). The study recommended several actions, including the necessity of holding training courses for employees in agile infrastructure projects on the effective use of AI applications and the use of AI technologies to analyze historical data to predict future needs and manage project schedules.