AI-Driven Decision Support for Project Risk Identification and Management Approach Selection

Abstract

The underperformance of projects has become a major source of economic losses across various industries, and often, it is due to poor identification of risk and the mismatch between the nature of the project and management approach adopted. Conventional approaches to risk management are based on high levels of expert opinion and stand-still assessment tools and therefore can be restrictive in terms of consistency and scalability in complex organizational settings. This research paper presents a decision-support system using artificial intelligence (AI) that combines project risk identification with the selection of an appropriate project management approach. The framework is based on a structured design science approach and an applied case study that shows how an AI-generated risk profiling can help inform the choice of predictive, adaptive, or hybrid project delivery models. The results indicate that AI based planning leads to greater transparency and more effective strategic alignment during the initial stages of a project, while also helping to identify and mitigate potential subjective biases in decision making. The research paper also contributes to the current body of research on digital transformation in project governance and provides practical implications for enhancing organizational efficiency and project performance. Although the findings are provisional and based on a small number of case studies, the framework provides a basis for future empirical validation across various industries.