This study attempts to develop a framework for implementing AI-based technologies to enhance knowledge management (KM) within project-based organizations. While AI offers numerous advantages, such as improved operational efficiency and advanced capabilities, its implementation in KM faces several challenges. Through interviews with nineteen experts in KM systems and AI technologies, the study identifies key challenges, including adaptation and usage challenges, ethical concerns, technical barriers, privacy issues, costs, and resistance to change. Ethical concerns about bias and accountability, along with technical issues related to data quality and infrastructure, further complicate AI implementation. The study also identifies enablers for successful AI implementation which include high-quality data, robust technology, strategic organizational planning, and maintaining human oversight. Effective change management strategies, such as comprehensive training, support, and promoting an open mindset, are essential for preparing individuals and teams for AI implementation.
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Bassam Hussein
Gizem Yildrim
Carsten Wolff
Procedia Computer Science
Norwegian University of Science and Technology
TU Dortmund University
Dortmund University of Applied Sciences and Arts
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Hussein et al. (Thu,) studied this question.
www.synapsesocial.com/papers/69c4cd05fdc3bde448918db4 — DOI: https://doi.org/10.1016/j.procs.2026.03.025