Artificial Intelligence-Based Predictive Analytics in Project Management: A Concept-Centric Systematic Literature Review
DOI:
https://doi.org/10.51137/wrp.ijarbm.629Keywords:
Artificial Intelligence, Predictive Analytics, Project Management, Machine Learning, Decision Support Systems, Risk PredictionAbstract
Artificial intelligence (AI)–based predictive analytics is increasingly applied in project management for schedule forecasting, cost estimation, risk prediction, and decision support optimisation. However, existing research remains fragmented across technical modelling studies, optimisation research, and socio-technical governance discussions. This study conducts a concept-centric systematic literature review of publications between 2020 and 2026 to synthesise the evolving knowledge base. The findings reveal three developmental phases: (i) early machine-learning models focused on delay and cost prediction, (ii) integration of optimisation-driven decision support systems, and (iii) generative AI environments accompanied by growing emphasis on explainability and governance. The review demonstrates that predictive analytics has evolved from a supplementary forecasting tool to a foundational intelligence layer embedded across the project life cycle. Despite technical advancement, fragmentation across life-cycle phases persist. The study proposes an integrated framework to guide future research on cross-phase integration, explainable AI, and human–AI collaboration in project environments.
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Copyright (c) 2026 Zainab Aziz, Tshilidzi Eric Nenzhelele (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
