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AI-driven project management: Challenges & oppportunities
Onyao, Lisa A. Zivak, Jovan Al Turk, Abdelhakim
Onyao, Lisa A.
Zivak, Jovan
Al Turk, Abdelhakim
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Original Date
Digitization Date
Issue Date
2025-06
Type
Article
Genre
Keywords
Artificial intelligence,Project management,Machine learning,Risk management,Process optimization
Subjects (LCSH)
Citation
Onyao, L. A., Zivak, J., Al Turk, A. (2025). AI-driven project management: Challenges & oppportunities. Journal of Management & Engineering Integration, 18(1), 14-22. https://doi.org/10.62704/10057/30201
Abstract
Project management (PM) has undergone significant transformation with the advancement of artificial intelligence (AI), which has introduced new capabilities for managing complex projects and streamlining processes. This paper aimed to explore the evolving role of AI in PM, highlighting key opportunities and obstacles for effective adoption. This paper addressed the successful integration of AI into PM by examining real scenarios that have occurred in various companies.
Table of Contents
Description
Published in SOAR: Shocker Open Access Repository by the Wichita State University Libraries Technical Services, August 2025.
Copyright of the Journal of Management and Engineering Integration is the property of the Association of Industry, Engineering and Management Systems Inc., and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.
Copyright of the Journal of Management and Engineering Integration is the property of the Association of Industry, Engineering and Management Systems Inc., and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.
Publisher
Association for Industry, Engineering and Management Systems (AIEMS)
Journal
Book Title
Series
Journal of Management & Engineering Integration
v.18 no.1
v.18 no.1
Digital Collection
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Use and Reproduction
Archival Collection
PubMed ID
ISSN
1939-7984