Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Ranah Research : Journal of Multidisciplinary Research and Development
Indriyani, Felia Sri
Unknown Affiliation
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Economics, Econometrics & Finance Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Transportation Other

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Maintaining Confidentiality and Security in the Utilization of Generative AI for IT Project Management Indriyani, Felia Sri; Raharjo, Teguh; Fitriani, Anita Nur
Ranah Research : Journal of Multidisciplinary Research and Development Vol. 8 No. 3 (2026): Ranah Research : Journal Of Multidisciplinary Research and Development
Publisher : Dinasti Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/rrj.v8i3.2072

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.
Co-Authors Fitriani, Anita Nur Raharjo, Teguh