International Journal of Scientific Research and Engineering Development

The decision activities carried out in electrical engineering projects are often complex in nature and involve consideration of various technical parameters, resource constraints, risk factors and dependencies of various projects in terms of scheduling. Conventional project management models are over-reliant on human judgment and the past experience, which might not be adequate in managing dynamic uncertainty, real-time data variability, and the magnitude of the current engineering projects. The new trends in artificial intelligence have brought about new possibilities in decision accuracy improvement by providing data-based insights and predictive modelling. This paper looks into the implementation of an AI-based hybrid decision system, which is a combination of expert knowledge structures and machine learning predictive analytics into the project management settings of electrical engineering projects. The suggested system will facilitate strategic and operational decision activities like estimating of costs, prioritization of resources, predicting risks, and optimization of schedules. The practice functioning and impact of the AI decision system are demonstrated with the help of a case application in a medium-scale electrical infrastructure project. The results show that there have been increased consistency in decisions, transparency in the project, and efficiency in executing projects with significant decrease in cost overrun and project delay. The research is relevant to the emerging literature on intelligent automation in the engineering profession and provides suggestions on how companies should adopt it, the way to implement systems, and how the research may be further developed in the future.

Muhammad Arsalan, Muhammad Ayaz, Yousaf Ali, Uroosa Baig ,"Integrating AI-Driven Decision Systems in Electrical Engineering Project Management" International Journal of Scientific Research and Engineering Development, V8(6): Page(2428-2439) Nov-Dec 2025. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.