Integrating Artificial Intelligence into Risk Management: A Holistic Framework for EPC Projects

Engineering, Procurement, and Construction (EPC) projects are characterized by high complexity, interdependencies, and exposure to various uncertainties. These features make effective risk management a critical factor for project success. Traditional risk management approaches often lack the adaptability and analytical depth required to handle dynamic project environments. This study proposes a holistic framework that leverages artificial intelligence (AI) to enhance the entire risk management process, including risk identification, assessment, prioritization, and mitigation. The proposed framework integrates machine learning techniques for predictive risk detection, natural hazard evaluation for quantitative analysis, and the intelligent algorithms for real-time risk evaluation and strategic decision support. By automating and improving the accuracy of risk-related decisions, the model enables project teams to respond proactively to emerging threats, minimize cost overruns and schedule delays, and improve overall project performance. Furthermore, the AI-driven approach supports adaptive learning, allowing continuous refinement of risk strategies based on updated data and evolving project conditions. The results suggest that the framework offers a practical, data-driven solution for managing risks in complex EPC projects, ultimately increasing resilience, efficiency, and the likelihood of project success.

کلیدواژه ها:

Artificial intelligence ، Risk management ، EPC projects ، Project risk assessment ، Machine learning