This thesis investigates the impact of Artificial Intelligence (AI) on modern project management processes by analyzing and incorporating existing research on the subject, focusing on how technologies such as Machine Learning (ML), Natural Language Processing (NLP), and Robotic Process Automation (RPA) have been applied to enhance predictive analytics, data-driven decision making, and intelligent automation within project management. The reviewed studies collectively indicate that AI improves project performance by enhancing forecasting accuracy, optimizing resource allocation, improved cost management, reliable risk management, and continuous project monitoring. AI tools also assist in automating repetitive administrative tasks, generating analytical insights, and supporting faster data-based decisions, allowing project managers to focus on stakeholder collaboration and team leadership. However, despite these benefits, the analysis also highlights several recurring challenges identified across literature, including high implementation costs, data quality and availability limitations, and organizational resistance to change. Furthermore, ethical concerns such as data privacy, accountability, bias, and job displacement need careful management and are crucial, requiring clear policies and strict governance. In summary, the research concluded that when utilized carefully and ethically, AI functions as a robust resource that complements human skills and transforms project management into a more responsive and insightful process.