The Reality of The Readiness of Some Countries in The Middle East and North Africa in Using Artificial Intelligence During The Period 2022-2024

  • Rima younes University of Algiers 3, Laboratory of Economic Transformation Strategies
Keywords: Artificial Intelligence, Government AI Readiness Index, National Strategies

Abstract

This study aims to analyze the strategies of selected Middle Eastern and North African countries,specifically the United Arab Emirates, the Kingdom of Saudi Arabia, and the State of Kuwait in the field of artificial intelligence adoption, with reference to the Government AI Readiness Index. The importance of this research lies in its attempt to link the strategic orientations of these countries with their institutional and technological readiness, while addressing a central question: To what extent do the strategies of Middle Eastern and North African countries reflect their level of readiness in the field of artificial intelligence according to the readiness index?

The findings indicate that the United Arab Emirates is the most advanced in terms of institutional and legislative frameworks, followed by Saudi Arabia due to its large-scale investments in infrastructure and research and development, while Kuwait has, in recent years, sought to establish a clearer national strategy. The results also reveal a gap between the declared ambitions and the actual level of readiness, primarily due to challenges related to human resources and regulatory frameworks. Accordingly, the study recommends intensifying regional cooperation and developing programs for digital capacity building, in order to enhance the sustainability of AI initiatives and ensure their alignment with global readiness standards.

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Published
2025-12-17
How to Cite
younes, R. (2025). The Reality of The Readiness of Some Countries in The Middle East and North Africa in Using Artificial Intelligence During The Period 2022-2024. Journal of Excellence for Economics and Management Research, 9(2), 147-166. Retrieved from http://journals.lagh-univ.dz/index.php/jeemr/article/view/4410
Section
Original Article