The Impact of Artificial Intelligence Applications in Non-Oil Sectors on Economic Diversification in the Gulf Cooperation Council Countries
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Abstract
This study examines how government readiness for artificial intelligence adoption influences the growth of non-oil sectors in the Gulf Cooperation Council (GCC) countries, situating this relationship within the broader framework of economic diversification. Given the persistent vulnerability of GCC economies to oil price volatility and geopolitical uncertainty, the research investigates whether AI adoption functions as a structural driver of diversified, sustainable growth rather than a purely technological add-on. Using a balanced panel dataset covering the six GCC states (UAE, Saudi Arabia, Kuwait, Bahrain, Oman, and Qatar) over the 2020 to 2024 period, the study applies panel data estimation techniques, testing pooled OLS, fixed effects, and random effects specifications. Diagnostic procedures, including the Redundant Fixed Effects test, the Hausman test, and Pesaran's cross-sectional dependence test, were used to select the most appropriate model, with results favoring the Pooled OLS specification. Findings indicate a statistically significant positive relationship between the government AI readiness index and non-oil sector growth, alongside a strong positive effect of overall GDP growth on non-oil output. These results suggest that institutional AI readiness has moved beyond symbolic policy commitments to generate measurable economic returns, helping to offset the region's historical dependence on hydrocarbon revenues. The study contributes a region-specific, multi-country econometric framework that extends prior descriptive and single-country research, offering policymakers empirical grounds for prioritizing AI integration as a lever for sustainable economic diversification across rentier economies.
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