Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
The Rise of Artificial Intelligence in Project Management: A Systematic Literature Review of Current Opportunities, Enablers, and Barriers
27
Zitationen
7
Autoren
2025
Jahr
Abstract
Artificial Intelligence (AI) and Machine Learning (ML) have transformed the landscape of project management and contributed significantly to improving efficiency, decision-making, and optimizing resource allocation. Although there exists a number of research examining the integration and utilization of AI and ML into project management, the fragmented literature highlights the need for a systematic literature review to consolidate current knowledge, identify emerging trends, and examine AI’s role in project management. This study aims to critically analyze the existing literature to identify opportunities for, enablers of, and barriers to AI adoption, providing a comprehensive framework to guide future research and practice. A systematic literature review (SLR) following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines revealed three key themes: The Knowledge Ecosystem in Project Management: In the Era of AI, The Intersection of AI and Humanity in Project Management, and Integrating AI into Project Management and Landscaping. The findings highlight AI’s transformative effects on forecasting accuracy, risk mitigation, stakeholder collaboration, and safety management while addressing challenges such as integration with legacy systems, data quality issues, and resistance to change. The research presents valuable insights for both researchers and practitioners, facilitating the navigation of adoption barriers, capitalizing on enablers, and unlocking AI’s potential to reshape project management practices across industries.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.231 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.084 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.444 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.423 Zit.