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Publications
Li. H., Yazdi, M., Nedjati, A., Moradi, R., Adumene, S., Dao, U., Moradi, AH., Haghighi, A., Obeng, F.E., Huang, C-G., Kang, H.S., Pirbalouti, R.G., Zarei, E., Dehghan, M., Darvishmotevali, M., Ghasemi, P., Fard, P.S. and Garg, H. (2024), Harnessing AI for project risk management: A paradigm shift, Progressive Decision-Making Tools and Applications in Project and Operation Management, Yazdi, M., (Ed.), Switzerland, Springer, pp. 253-272.
Project risk management is pivotal in ensuring the success of endeav-ours within contemporary organizations. As businesses navigate an intricate and competitive landscape, integrating artificial intelligence (AI) introduces a paradigm shift in how project risks are recognized, evaluated, and addressed. This chapter go through into the multifaceted impact of AI on project risk management, reshaping strategies and enhancing decision-making processes to elevate project outcomes. By leveraging predictive analytics and machine learning, AI uncovers hidden patterns in historical project data, enabling proactive risk anticipation and simulation-based mitigation strategies. AI’s cognitive capabilities expedite risk assessment by aggre-gating diverse data sources, fostering agility in response strategies through real-time communication and collaboration among project teams. Beyond operational facets, AI-driven algorithms continuously adapt to evolving risk landscapes, refining risk management strategies and resource allocation. Ethical considerations arise with the expanding role of AI, emphasizing the importance of transparency and accountability in algorithmic decision-making. This chapter envisions a dynamic convergence of AI and project risk management, fostering a future where innovation harmonizes with human understanding, propelling projects towards excellence, resilience, and growth.
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