Artificial intelligence in the United Arab Emirates public sector: A systematic literature review
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...
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| Format: | Article |
| Language: | English |
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Institute of Advanced Engineering and Science
2024
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| Online Access: | http://umpir.ump.edu.my/id/eprint/44612/ http://umpir.ump.edu.my/id/eprint/44612/1/Artificial%20intelligence%20in%20the%20United%20Arab%20Emirates%20public%20sector.pdf |
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| author | Akhoirshieda, Modafar Shaker Ku Muhammad Naim, Ku Khalif Suryanti, Awang |
| author_facet | Akhoirshieda, Modafar Shaker Ku Muhammad Naim, Ku Khalif Suryanti, Awang |
| author_sort | Akhoirshieda, Modafar Shaker |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-15T03:56:00Z |
| format | Article |
| id | ump-44612 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:56:00Z |
| publishDate | 2024 |
| publisher | Institute of Advanced Engineering and Science |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-446122025-05-21T08:57:55Z http://umpir.ump.edu.my/id/eprint/44612/ Artificial intelligence in the United Arab Emirates public sector: A systematic literature review Akhoirshieda, Modafar Shaker Ku Muhammad Naim, Ku Khalif Suryanti, Awang QA Mathematics QA75 Electronic computers. Computer science 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. Institute of Advanced Engineering and Science 2024 Article PeerReviewed pdf en cc_by_sa_4 http://umpir.ump.edu.my/id/eprint/44612/1/Artificial%20intelligence%20in%20the%20United%20Arab%20Emirates%20public%20sector.pdf Akhoirshieda, Modafar Shaker and Ku Muhammad Naim, Ku Khalif and Suryanti, Awang (2024) Artificial intelligence in the United Arab Emirates public sector: A systematic literature review. IAES International Journal of Artificial Intelligence, 13 (3). 2472 -2481. ISSN 2089-4872. (Published) http://doi.org/10.11591/ijai.v13.i3.pp2472-2481 http://doi.org/10.11591/ijai.v13.i3.pp2472-2481 |
| spellingShingle | QA Mathematics QA75 Electronic computers. Computer science Akhoirshieda, Modafar Shaker Ku Muhammad Naim, Ku Khalif Suryanti, Awang Artificial intelligence in the United Arab Emirates public sector: A systematic literature review |
| title | Artificial intelligence in the United Arab Emirates public sector: A systematic literature review |
| title_full | Artificial intelligence in the United Arab Emirates public sector: A systematic literature review |
| title_fullStr | Artificial intelligence in the United Arab Emirates public sector: A systematic literature review |
| title_full_unstemmed | Artificial intelligence in the United Arab Emirates public sector: A systematic literature review |
| title_short | Artificial intelligence in the United Arab Emirates public sector: A systematic literature review |
| title_sort | artificial intelligence in the united arab emirates public sector: a systematic literature review |
| topic | QA Mathematics QA75 Electronic computers. Computer science |
| url | http://umpir.ump.edu.my/id/eprint/44612/ http://umpir.ump.edu.my/id/eprint/44612/ http://umpir.ump.edu.my/id/eprint/44612/ http://umpir.ump.edu.my/id/eprint/44612/1/Artificial%20intelligence%20in%20the%20United%20Arab%20Emirates%20public%20sector.pdf |