Enhancing Engineering Productivity with AI-Integrated Workforce Management Systems

Abstract

The integration of Artificial Intelligence (AI) in workforce management is transforming engineering project execution by optimizing manpower allocation and resource utilization. This research presents an AI-enabled system leveraging Microsoft Power Apps, SharePoint, and Power BI to streamline engineering workforce management. The proposed framework enables real-time tracking of projects, classification of tasks, monitoring of engineering hours, and identification of key resources based on skillsets and workload. By utilizing data-driven decision-making and interactive dashboards, the system enhances efficiency, minimizes resource bottlenecks, and improves project execution. The study highlights the benefits of AI-powered automation in manpower planning, project prioritization, and operational efficiency. The findings demonstrate the system’s potential in reducing workload imbalance, improving productivity, and enhancing data visualization for informed decision-making.