Maintaining Confidentiality and Security in the Utilization of Generative AI for IT Project Management
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Published
May 19, 2026
Abstract
The use of Generative AI has become a growing trend in project management, supporting activities such as learning, document preparation, and decision-making. However, its adoption also raises concerns related to confidentiality and security due to the involvement of sensitive project data. Therefore, this study examines how Generative AI can be safely utilized across PMBOK Knowledge Areas in IT project management while maintaining data confidentiality and security. The research was conducted in two stages. The first stage involved two systematic literature reviews following the Kitchenham method: one examining the utilization of Generative AI in project management (17 primary studies) and another focusing on ethical considerations, policy implications, and data security issues related to Generative AI (36 primary studies). The second stage involved an expert assessment with five experts to evaluate the applicability of Generative AI across PMBOK Knowledge Areas, identify relatively safe input types, and determine key considerations for maintaining confidentiality and security. The results indicate that Generative AI can be applied across all PMBOK Knowledge Areas, however not all input types and information are considered safe. Text identified as the safest, source code as high-risk, confidential data as unsuitable for sharing, and privacy and data protection as the primary concern.
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How to Cite
Indriyani, F. S., Raharjo, T. and Fitriani, A. N. (2026) “Maintaining Confidentiality and Security in the Utilization of Generative AI for IT Project Management ”, Ranah Research : Journal of Multidisciplinary Research and Development, 8(3), pp. 1926-1941. doi: 10.38035/rrj.v8i3.2072.
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Korzyński, P., Susana Costa e, S., Anna Maria, G., & Mazurek, G. (2024). Trust in AI and Top Management Support in Generative-AI Adoption. Journal of Computer Information Systems, 1–15. https://doi.org/10.1080/08874417.2024.2401986
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Kumar, S., & Malhotra, D. (2025). Dark side of generative AI in tourism: a stressor-strain-outcome perspective; using a mixed-methods approach. Tourism Recreation Research, 1–14. https://doi.org/10.1080/02508281.2025.2503997
Kumar, V., Kotler, P., Gupta, S., & Rajan, B. (2024). Generative AI in Marketing: Promises, Perils, and Public Policy Implications. Journal of Public Policy & Marketing, 44(3), 309–323. https://doi.org/10.1177/07439156241286499
Lao, Y., & You, Y. (2024). Unraveling generative AI in BBC News: application, impact, literacy and governance. Transforming Government: People, Process and Policy. https://doi.org/10.1108/TG-01-2024-0022
Lin, Z., & Ng, Y.-L. (2024). Unraveling Gratifications, Concerns, and Acceptance of Generative Artificial Intelligence. International Journal of Human–Computer Interaction, 1–18. https://doi.org/10.1080/10447318.2024.2436749
Liu, J. (2025). Applying Ethics of Care-Based Response Strategies to Mitigate AI-Related Corporate Crisis: The Moderating Role of Crisis Involvement. International Journal of Strategic Communication, 19(2), 130–157. https://doi.org/10.1080/1553118X.2025.2459609
Liu, Y., & Du, Y. (2025). The Effect of Generative AI Ethics on Users’ Continuous Usage Intentions: A PLS-SEM and fsQCA Approach. International Journal of Human–Computer Interaction, 1–12. https://doi.org/10.1080/10447318.2025.2465861
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Nafil, K., & Lefdaoui, Y. (2024). Innovative Approach to Agile Education: Generative AI-Supported Planning Poker Simulation. 2024 21st International Conference on Information Technology Based Higher Education and Training (ITHET), 1–6. https://doi.org/10.1109/ITHET61869.2024.10837671
Niu, B., & Mvondo, G. F. N. (2024). I Am ChatGPT, the ultimate AI Chatbot! Investigating the determinants of users’ loyalty and ethical usage concerns of ChatGPT. Journal of Retailing and Consumer Services, 76, 103562. https://doi.org/10.1016/j.jretconser.2023.103562
Nyqvist, R., Peltokorpi, A., & Seppänen, O. (2024). Can ChatGPT exceed humans in construction project risk management? Engineering, Construction and Architectural Management, 31(13), 223–243. https://doi.org/10.1108/ECAM-08-2023-0819
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