Review of AI in Project Management and Conceptual Analysis on Risk Management

Project management is becoming a critical activity for the enterprises as the resources are getting limited and scarce. It seems Artificial Intelligence (AI) will be providing effective utilization of resources and enabling easy operations with human like operations, machine learning, intelligent agents, fuzzy logic and other AI methodologies provide effective data analysis and automation to enhance of project planning, execution, and monitoring. The paper reviews some of the AI application in these areas. AI cam also play a critical role in risk management and contingency planning, in order to identify and mitigate potential obstacles. A conceptual analysis along this line is also provided in the paper. Since AI is well known for automating routine tasks, streamlining workflows, and improving resource utilization, easing resource allocation and improving both efficiency and effectiveness for other domains, it could very well be implemented in project management domains. As explained in the paper respective literature and previous research encourage this kind of studies. While AI holds immense potential in project management, some technical improvement is necessary. There is a need for defining conceptual analysis and implementable models for basic project management activities. It is also very imminent that the ethical considerations, data privacy, and the need for human-AI collaboration should not be overlooked. In conclusion, AI-based PM represents a paradigm shift in the field. This has to be formulated to easy the respective development activities. Considering the complexity in risks and uncertainties, resource controls, schedule, stakeholder and scope management, the research shows that using artificial intelligence in project management will provide many benefits to project managers. This article is an attempt to explore the multifaceted role of AI in PM, investigating its core components, applications, benefits, and challenges. It specifically takes the attention to risk management with respective agent architecture and responsibilities.