The successful adoption of programmable machines for complex tasks opens up opportunities for productivity and more efficient communication, but also poses serious challenges in IT project management. This study aims to tackle the issue of high project failure rates caused by inadequate planning. It aims to assist project managers in enhancing their project planning by implementing real-time solutions through the utilization of machine learning (ML) algorithms and a user-friendly graphical interface. This research is divided into two key phases. The initial phase involves an examination of existing literature in the field of machine learning to identify relevant concepts applicable to project management. In the subsequent stage, two distinct types of ML algorithms, namely example-based learning and regression modeling, will be integrated into a user-friendly platform. This research develops a system that utilizes machine learning algorithms to assist project managers in real-time or near real-time through a user-friendly graphical interface, with a focus on improving project planning and risk mitigation. This research shows that machine learning algorithms provide positive results in overcoming human factors and preventing risks based on the experience of project managers.
