Investigating risk elements and critical success factors for AI procurement projects in the public sector: a qualitative approach based on UAE public organisations

Khalid Alshehhi (), Ali Cheaitou and Hamad Rashid
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Khalid Alshehhi: University of Sharjah
Ali Cheaitou: University of Sharjah
Hamad Rashid: University of Sharjah

International Journal of System Assurance Engineering and Management, 2025, vol. 16, issue 2, No 2, 446-467

Abstract: Abstract This study identifies the risk elements and critical success factors in procuring artificial intelligence (AI) projects, focusing on the public sector in the United Arab Emirates (UAE). On the basis of literature, major risk factors were identified. Then, a qualitative study covered 15 AI projects in public sector organisations in UAE. Forty experts from these organisations shared their experiences of different risks in procuring AI projects through in-depth, semi-structured interviews, which were then analysed thematically. Results indicated that the procured projects involved different types of risks categorised as procurement-dimension-related risks and technology-dimension-related risks. The risks relating to the procurement dimension are vendor risk, financial risk, legal risk, risk of time frame, and risk of miscommunication. The risks concerning technology dimension are privacy and security risks, ethical risk, integration risk, skills risk, environmental risk, and risk of system malfunction. The critical success factors are categorised as AI capabilities, governance, and AI risk management.

Keywords: AI procurement; UAE public sector; Risk elements; Critical success factor; AI risk management (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s13198-024-02653-9

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