Artificial Intelligence and Machine Learning Approaches for Managing Complex Project in Dynamic Environments

Abstract

The growing sophistication and ambiguity of the modern project settings require adopting the latest technologies to aid in decision-making and risk reduction. AI and ML appear to be the disruptive technology in project management offering solutions that are based on data and increase the efficiency and effectiveness of project management of complex projects. This paper discusses the use of AI and ML methods in dynamic project settings and how the tools optimize resource allocation, project outcomes, and risks in real-time. Using a review of existing literature on the topic and case studies, the article brings out the challenges and opportunities of these technologies in enhancing the performance of projects. Predictive analytics, deep learning, reinforcement learning, and natural language processing are considered to be among the key techniques that can be used to adapt to evolving conditions of projects and make more informed decisions. Another issue that the article addresses is the proposal of integrating AI and ML with traditional project management frameworks, as well as, the proposal of a conceptual model of how these two can be implemented. Finally, the evidence indicates that AI and ML can be important in handling the dynamics of contemporary projects, providing huge gains in delivering projects, cost management, and risk management.