New approaches to risk management in IT projects with high uncertainty

Abstract

Risk management has become an increasingly critical component of successful IT project execution, particularly in environments marked by high levels of uncertainty. Traditional risk management models, while widely used, often lack the flexibility and predictive capabilities needed to address the challenges of complex, dynamic IT projects. Recognizing this gap, the present study proposes the development of an integrated risk management framework that combines the structural strengths of internationally recognized standards—namely ISO 31000 and COSO ERM—with innovative, technology-driven approaches such as Artificial Intelligence (AI), Digital Twins, and Behavioural Science. These tools are intended to provide real-time insights, enhance foresight, and support proactive decision-making. To support the creation and validation of this framework, a detailed analysis of existing standards and methodologies was conducted, along with a review of future trends in the risk management field. The research follows a Design Science Research approach to iteratively design, refine, and evaluate the proposed framework. The outcome is a model that offers greater adaptability, improved collaboration across organizational levels, and enhanced cost efficiency in resource allocation. A validation process was conducted to assess its effectiveness, with findings confirming its practical value while also identifying areas—such as scalability and implementation guidance—that require further refinement. This work contributes to the ongoing evolution of project risk management by offering a robust and forward-looking tool that organizations can adapt to better navigate risk in uncertain and complex IT project environments.