An Interactive and Adaptive AI-based Decision Support System for Dynamic Risk Management in Megaprojects
Keywords:
Megaprojects, as vital instruments of societal and infrastructural transformation, are often challenged by cost overruns, delays, and evolving risks—issues that can compromise both their immediate success and long-term sustainability. Traditional risk management approaches, grounded in static and reactive frameworks, fall short in addressing the complexity and dynamism of such large-scale initiatives. This position paperproposes an Interactive and Adaptive AI-based Decision SupportSystem (DSS) that integrates Interactive Machine Learning(IML) and Adaptive Deep Learning with domain expert input. Central to this approach is the concept of hybrid intelligence, where AI-driven analytics and human judgment are combined synergistically to enhance decision-making. The system embedsexpert-in-the-loop mechanisms to enable continuous, contextaware learning from both historical data and real-time feedback. This produces interpretable, real-time insights for proactive risk identification, assessment, and forecasting. The hybrid intelligence framework promotes greater resilience, adaptability, andtransparency—contributing to more sustainable, informed, andethically responsible governance of complex megaprojects.