Author's: Raed Atef
Affilation: Independent Researcher Palestine
Volume 1, Issue 1, 2026 | Pages: 54–68 |
Google scholar link → Download PDFArtificial intelligence (AI) is increasingly reshaping economic development across the Gulf Cooperation Council (GCC), delivering significant productivity gains while simultaneously intensifying inequality, labour market polarization, and unequal access to digital resources. Although existing research explains these outcomes through either technological diffusion or institutional factors, it rarely examines how these dimensions interact. This paper addresses this gap by developing an integrated explanation of how AI-driven transformation generates uneven economic outcomes in GCC economies. The study adopts a conceptual, theory-building methodology based on analytical synthesis rather than empirical testing. It integrates insights from digital economy transformation, inclusive growth theory, socio-technical systems, and environmental, social, and governance (ESG) frameworks. Using mechanism-based reasoning, these perspectives are unified into the Triadic AI-Inclusive Growth Model (TAIGM), which is structured around three interdependent capacities: innovation, inclusion, and governance–sustainability. The findings conceptualize AI-driven inequality as an endogenous outcome of misalignment among these three capacities. When innovation advances faster than inclusion and governance adaptation, a dual-speed digital economy emerges, where high-productivity sectors rapidly capture AI benefits while other sectors remain structurally excluded or lag behind. In this view, economic outcomes are shaped less by technology diffusion itself and more by the degree of systemic alignment across institutional and socio-economic capacities. As a conceptual study, the TAIGM framework is not yet empirically validated. Future research should operationalize key constructs such as inclusion capacity and governance responsiveness and test their interaction effects using cross-country datasets, panel econometric techniques, or system dynamics modelling in AI-driven economies. Despite this limitation, the study contributes a mechanism-based framework that reconceptualizes inequality as a systemic consequence of AI transformation, advancing theoretical debates on inclusive and sustainable digital development in emerging economies.
Artificial intelligence; Gulf Cooperation Council (GCC); digital economy; inclusive growth; ESG; digital inequality.
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