Using Artificial Intelligence in Engineering Project Management
Keywords:
AI, Engineering PM, ML, Integrated Analytics, Risk Assessment, Extensive Cost-Saving, Efficiency in Time, Resource Utilization, Complexity, AI IntegrationAbstract
This research aimed to determine the interaction and effects of AI applications in engineering project management on cost, time, risk, and resources. Focusing on survey data collected from project managers and engineers working in engineering firms currently implementing AI tools to accomplish construction project tasks, the study explores AI applications such as machine learning, predictive analytics, and natural language processing. The implementation and application of AI positively influence project performance by minimizing cost, scheduling issues, and resource allocation issues. This means that though there is potential for future cost reduction since the use of AI would require long-term costs to be reduced in the future, the initial costs of implementing AI and the costs incurred by employees in training are a hurdle. As implemented in the study, the AI tool application is aligned with benefits such as better cost, time control, and risk management for properly optimizing project resources. They also highlighted the regression analysis conclusions, which proved that cost reduction results from the AI tool usage and project complexity are still the main factors deciding the costs. Based on the findings, the following recommendations are offered to engineering firms to enhance the use of AI in the projects. First and foremost, engineering firms should allocate more resources towards training the human capital that will work on implementing AI within the company.
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