Artificial intelligence and the Gulf Cooperation Council workforce adapting to the future of work

• URL: http://arxiv.org/abs/2511.05927v1
• Date: Sat, 08 Nov 2025 08:42:14 GMT
• Title: Artificial intelligence and the Gulf Cooperation Council workforce adapting to the future of work
• Authors: Mohammad Rashed Albous, Melodena Stephens, Odeh Rashed Al-Jayyousi,
• Abstract summary: The rapid expansion of artificial intelligence (AI) in the Gulf Cooperation Council (GCC) raises a central question: are investments in compute infrastructure matched by a robust build-out of skills, incentives, and governance?<n>This study audits workforce preparedness across Kingdom of Saudi Arabia (KSA), United Arab Emirates (UAE), Qatar, Kuwait, Bahrain, and Oman.<n>We identify an emerging two-track talent system, research elites versus rapidly trained practitioners, that risks labor-market bifurcation without bridging mechanisms.
• Score: 0.5735035463793009
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The rapid expansion of artificial intelligence (AI) in the Gulf Cooperation Council (GCC) raises a central question: are investments in compute infrastructure matched by an equally robust build-out of skills, incentives, and governance? Grounded in socio-technical systems (STS) theory, this mixed-methods study audits workforce preparedness across Kingdom of Saudi Arabia (KSA), the United Arab Emirates (UAE), Qatar, Kuwait, Bahrain, and Oman. We combine term frequency--inverse document frequency (TF--IDF) analysis of six national AI strategies (NASs), an inventory of 47 publicly disclosed AI initiatives (January 2017--April 2025), paired case studies, the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) and the Saudi Data & Artificial Intelligence Authority (SDAIA) Academy, and a scenario matrix linking oil-revenue slack (technical capacity) to regulatory coherence (social alignment). Across the corpus, 34/47 initiatives (0.72; 95% Wilson CI 0.58--0.83) exhibit joint social--technical design; country-level indices span 0.57--0.90 (small n; intervals overlap). Scenario results suggest that, under our modeled conditions, regulatory convergence plausibly binds outcomes more than fiscal capacity: fragmented rules can offset high oil revenues, while harmonized standards help preserve progress under austerity. We also identify an emerging two-track talent system, research elites versus rapidly trained practitioners, that risks labor-market bifurcation without bridging mechanisms. By extending STS inquiry to oil-rich, state-led economies, the study refines theory and sets a research agenda focused on longitudinal coupling metrics, ethnographies of coordination, and outcome-based performance indicators.

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