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◆ SAGE Open2025-10-01· Structural equation modeling

Exploring the Determinants of Artificial Intelligence Adoption Intention in the SMEs of United Arab Emirates

George Thomas, Norah Albishri, Jamid Ul Islam, Muhammad Tanveer

原始摘要(英文原文)· Original abstract
The global business landscape is currently experiencing a transformative shift propelled by technological advancements, particularly Artificial Intelligence, which is reshaping operations and enhancing organizational capabilities. This paper investigates the adoption intention of AI within the Small and Medium Enterprises in the United Arab Emirates, a country recognized for its embrace of technological innovation. Addressing a key research gap, the study emphasizes the limited exploration of AI adoption determinants within SMEs in emerging economies. Built on the application of the technology–organization–environment framework and integrating the Technology Acceptance Model, the research identifies factors influencing AI adoption intention in UAE hospitality SMEs. A quantitative survey of 315 respondents was conducted, and data were analyzed using structural equation modeling (SEM) in SmartPLS. The findings reveal significant relationships between perceived competitive advantage, perceived usefulness, perceived top management support, perceived employee capability, perceived competitive pressure, perceived government regulations and AI adoption intention, affirming the validity of the proposed conceptual model. The results further show that organizational (top management support) and environmental factors (competitive pressure, government regulation) exert stronger influence than technological perceptions, highlighting the role of leadership and institutional pressures in shaping adoption. The study contributes theoretically by contextualizing TOE–TAM integration and practically by offering actionable insights for SME leaders, policymakers, and stakeholders to drive AI adoption.
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