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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Naim Ku Khalif, Ku Muhammad
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Computer Science & IT Engineering

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Artificial intelligence in the United Arab Emirates public sector: a systematic literature review Akhoirshieda, Modafar Shaker; Naim Ku Khalif, Ku Muhammad; Awang, Suryanti
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i3.pp2472-2481

Abstract

This systematic literature review examines United Arab Emirates (UAE) public sector artificial intelligence (AI) use, impact, and challenges. Using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) protocol, 20 relevant Scopus articles were selected for the study. Data from selected articles were used to analyse AI's use, benefits, and drawbacks in the UAE's public sector. Quality assessment was done throughout the review process. The results showed that AI is being used more in the UAE's public sector to improve efficiency, cost savings, decision-making, and service delivery. The review also found data, privacy, security, technical, infrastructure, AI, and user challenges. Publication bias and the lack of AI studies in the UAE's public sector limit the study. The findings have major implications for policy and practice, emphasising the need for AI strategies and UAE-specific solutions.
Co-Authors Akhoirshieda, Modafar Shaker Awang, Suryanti