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Challenges of AI Adoption in the UAE Healthcare

Author

Listed:
  • Fatma Khamis Al Badi
  • Khawla Ali Alhosani
  • Fauzia Jabeen
  • Agata Stachowicz-Stanusch
  • Nazia Shehzad
  • Wolfgang AMANN

Abstract

The purpose of this study is to prioritize the challenges of adopting Artificial Intelligence (AI) in the healthcare sector of the United Arab Emirates (UAE). An Analytic Hierarchy Process (AHP) method was used, and the data were collected from the managerial-level executives ( n = 27) involved in AI adoption in their respective healthcare organizations. The results prioritized the AI main criteria and sub-criteria based on their priority weights in the healthcare sector. The results also revealed that accuracy, privacy and security criteria are the most important factors to optimize the healthcare sector with AI. The research findings shall help policymakers formulate suitable strategies with current adoption and acceptance of AI in the healthcare sector. The findings will help policymakers utilize this study’s outcomes to create a well-defined picture of AI’s actual adoption and acceptance in the healthcare sector.

Suggested Citation

  • Fatma Khamis Al Badi & Khawla Ali Alhosani & Fauzia Jabeen & Agata Stachowicz-Stanusch & Nazia Shehzad & Wolfgang AMANN, 2022. "Challenges of AI Adoption in the UAE Healthcare," Vision, , vol. 26(2), pages 193-207, June.
    • Handle: RePEc:sae:vision:v:26:y:2022:i:2:p:193-207
    DOI: 10.1177/0972262920988398
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    References listed on IDEAS

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    1. Saaty, Thomas L., 1990. "How to make a decision: The analytic hierarchy process," European Journal of Operational Research, Elsevier, vol. 48(1), pages 9-26, September.
    2. David Thesmar & David Sraer & Lisa Pinheiro & Nick Dadson & Razvan Veliche & Paul Greenberg, 2019. "Combining the Power of Artificial Intelligence with the Richness of Healthcare Claims Data: Opportunities and Challenges," PharmacoEconomics, Springer, vol. 37(6), pages 745-752, June.
    3. Muna Al Suwaidi & Fauzia Jabeen & Agata Stachowicz-Stanusch & Matthew Webb, 2020. "Determinants Linked to Executive Succession Planning in Public Sector Organizations," Vision, , vol. 24(3), pages 284-299, September.
    4. Young-Joo Lee & Ji-Young Park, 2018. "Identification of future signal based on the quantitative and qualitative text mining: a case study on ethical issues in artificial intelligence," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(2), pages 653-667, March.
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