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Artificial intelligence in the United Arab Emirates public sector: a systematic literature review

IAES International Journal of Artificial Intelligence · Vol. 13 No. 3 (2024) · hlm. 2472–2481

DOI
10.11591/ijai.v13.i3.pp2472-2481
ISSN
2252-8938, 2089-4872
Terbit
2024-09-01
Penerbit
Institute of Advanced Engineering and Science
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

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.

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19 penulis · 54 tautan kepenulisan bersama · 27 lintas organisasi

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  • Universiti Malaysia Pahang Al-Sultan Abdullah
  • International Islamic University Malaysia
  • Universiti Teknologi MARA
  • Institut Teknologi Sepuluh Nopember
  • Northumbria University
  • Universiti Sains Islam Malaysia
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  • Organisasi berbeda
  • Organisasi sama
  • Afiliasi tidak diketahui
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Tampilkan sebagai tabel
Rekan penulisOrganisasiArtikel bersama
Nur Azri ShaharuddinAfiliasi tidak diketahui1
Asmarani Ahmad PuziInternational Islamic University Malaysia1
Amelia Ritahani IsmailInternational Islamic University Malaysia1
Ahsiah IsmailInternational Islamic University Malaysia1
Muhammad Afiq Mohd AraInternational Islamic University Malaysia1
Roziana RamliNorthumbria University1
Mohammad Isa IrawanInstitut Teknologi Sepuluh Nopember1
Mohammad Ashraf IqbalInstitut Teknologi Sepuluh Nopember1
Noryanti MuhammadUniversiti Malaysia Pahang Al-Sultan Abdullah1
Mohd Khairul Bazli Mohd AzizUniversiti Malaysia Pahang Al-Sultan Abdullah1
Muhammad Nanda SetiawanInstitut Teknologi Sepuluh Nopember1
Nurazzah Abd RahmanUniversiti Teknologi MARA1
Shaiful Bakhtiar bin RodzmanUniversiti Teknologi MARA1
Normaly Kamal IsmailUniversiti Teknologi MARA1
Syed Ahmad AljunidUniversiti Teknologi MARA1
Zulhilmi Mohamed NorUniversiti Sains Islam Malaysia1

Afiliasi berasal dari OpenAlex; metadata OAI-PMH jurnal tidak memuatnya. Penulis tanpa ID OpenAlex dicocokkan berdasarkan nama, sehingga dua orang bisa tergabung atau satu orang bisa terpisah.

Sumber metadata: OAI-PMH (metadata jurnal) http://ijai.iaescore.com/index.php/IJAI/oai, pertama di-harvest 8 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">Artificial intelligence in the United Arab Emirates public sector: a systematic literature review</dc:title>
	<dc:creator>Akhoirshieda, Modafar Shaker</dc:creator>
	<dc:creator>Naim Ku Khalif, Ku Muhammad</dc:creator>
	<dc:creator>Awang, Suryanti</dc:creator>
	<dc:subject xml:lang="en-US">Artificial Intelligence, Decision making, public sector</dc:subject>
	<dc:subject xml:lang="en-US">Artificial intelligence; Decision support system; Emerging technology; Public sector; Systematic literature review; United Arab Emirates</dc:subject>
	<dc:description xml:lang="en-US">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.</dc:description>
	<dc:publisher xml:lang="en-US">Institute of Advanced Engineering and Science</dc:publisher>
	<dc:contributor xml:lang="en-US">Centre for Mathematical Sciences, College of Computing &amp; Applied Sciences, Universiti Malaysia Pahang (UMP), Phang, Malaysia</dc:contributor>
	<dc:date>2024-09-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US"></dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ijai.iaescore.com/index.php/IJAI/article/view/24165</dc:identifier>
	<dc:identifier>10.11591/ijai.v13.i3.pp2472-2481</dc:identifier>
	<dc:source xml:lang="en-US">IAES International Journal of Artificial Intelligence (IJ-AI); Vol 13, No 3: September 2024; 2472-2481</dc:source>
	<dc:source>2252-8938</dc:source>
	<dc:source>2089-4872</dc:source>
	<dc:source>10.11591/ijai.v13.i3</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ijai.iaescore.com/index.php/IJAI/article/view/24165/14051</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2024 Institute of Advanced Engineering and Science</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>