Artificial Intelligence in project risk management: A systematic literature review
Year: 2025
Type: review
Study design: Systematic Review
Abstract: In an increasingly dynamic and uncertain global environment, organizations seek advanced methods to enhance project success and resilience. This dissertation investigates how Artificial Intelligence (AI) can improve Project Risk Management (PRM) by systematically analyzing peer-reviewed research published between 2018 and mid-2025. A Systematic Literature Review (SLR) based on the PRISMA methodology and aligned with the PMI (2019) Standard for Risk Management and ISO31000 (2018) guidelines, was conducted across Scopus, Web of Science, and IEEE Xplore, retrieving 109 records. After multi-stage screening, 57 documents were retained for detailed analysis, and the 20 most-cited studies (18 articles + 2 books) formed the final analysis document set. The findings reveal that AI, particularly machine learning, Bayesian networks, neural networks, and natural language processing, strengthens traditional PRM by improving risk identification, assessment, and monitoring. AI contributes to predictive accuracy, analytical precision, and decision transparency, yet challenges remain regarding data fragmentation, explainability, and ethical constraints. The results support a hybrid human–AI risk-governance paradigm, where algorithmic intelligence complements managerial judgment. In the end, this research tries to contribute theoretically, methodologically, and practically to understanding how AI can redefine project-risk practices.
Source: Repositório do ISCTE-IUL
Author: Lopes, Ricardo Salgado
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7219323886