A Systematic Short Review of Machine Learning and Artificial Intelligence Integration in Current Project Management Techniques

In the ever-evolving landscape of project management, integrating machine learning (ML) and artificial intelligence (AI) within contemporary project management software (PMS) is a transformative frontier that holds significant promise. As the complexity and scope of a project develop, conventional approaches can encounter difficulties in delivering the required agility and predictive skills. ML and AI provide sophisticated data analysis, predictive modeling, and automation capabilities that enable enterprises to efficiently utilize resources, proactively identify hazards, and effectively respond to evolving needs. This connection provides project managers with practical information and allows them to make decisions based on data in high-speed contexts. This short systematic literature review (SLR) rigorously analyzes the present level of ML integration in PMS. The inquiry involves formulating research inquiries, devising a comprehensive search plan, selecting rigorous studies, and integrating data according to a well-defined review methodology that is influenced by established norms. This short review outlines the primary domains in which ML improves project management, emphasizes the practical difficulties encountered, and reveals the growing patterns of incorporating cutting-edge technology. We present a strategic framework for guiding future research directions, providing a basis for practitioners and scholars to comprehend the significant influence of integrating ML and AI on project management. In essence, this study highlights the capacity of ML and AI to revolutionize project management by enabling the discovery of novel efficiencies, enhancing the decision- making process, and fundamentally altering the administration of projects in a world driven by data.