Augmented Project Management: Exploring the Role of AI Tools in Decision-making and Resource Optimisation
Ogochukwu Gold Abaneme *
College of Professional Studies, Roux Institute, Northeastern University, USA.
Chiamaka Ezenwaka
Department of Marketing Analytics and Insights, Wright State University, USA.
Raphael Popoola
Caterpillar Inc, United States.
Olabode Soetan
Department of Tax Technology Consulting Practice, Deloitte LLP, USA.
Henry Asusheyi Obajaja
Department Health and Human Performance and Recreation, University of Arkansas, USA.
Elizabeth Umah
Department of Information Systems and Business Analytics, Florida International University, USA.
*Author to whom correspondence should be addressed.
Abstract
Background: Project management is defined as the planning, execution, and monitoring of projects to meet predefined objectives/success criteria while adhering to specified time, budget, and scope constraints and is crucial to successful business. Conventional project management processes have been largely dependent on human expertise and manual processes, but, due to increasing project complexity as a result of globalisation, technological advancement and more sophisticated client demands, conventional methods are also seen as having limitations.
Aim: This review aims to discuss the disruptive capabilities of AI on in the field of project management with an emphasis on the use of AI instruments to help decision making, resource deployment and risk handling within complicated projects.
Methodology: The paper consisted of a review of studies, case studies and tools deployed within multiple sectors, including construction, IT and Healthcare, in academic articles. Reports produced between the years of 2015-2025 were included.
Results: AI applications have transformed the manner in which projects are managed, specifically by revolutionising how projects deal with resource allocation, risk and decision making. Decision making can be improved through the use of data-driven insights from predictive analytics and automatic learning of machine algorithms, serving to reduce the role of human error and predicting project trends. Forecast, LiquidPlanner, Smartsheet, and other similar AI-driven software applications assist in scheduling projects and managing resources. AI tools further reduce the administrative burden, support collaborative teamwork, and automate repetitive tasks. On top of that, the case studies of Bechtel and Fluor, among others, reveal the actual advantages AI brings to decrease project costs, resource allocations, and overall project performance.
Conclusion: The use of AI tools has changed the face of project management, hugely improving efficiency and decision-making and overall risk management. Additional studies should assess the ethical implications of AI and the future implications of projects. The future of AI in project management is optimistic, and, as technologies progress, it is likely to impact project management by making projects more efficient, sustainable, and economical throughout industries.
Keywords: Artificial Intelligence (AI), project management, resource optimisation, decision-making, risk management