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

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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Publication Details

Journal
SAGE Open
Published
2025-10-01
DOI
https://doi.org/10.1177/21582440251395561
Primary Topic
Organizational and Employee Performance
Type
article
Field-Weighted Citation Impact
0.00
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article

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

George Thomas, Jamid Ul Islam, Norah Albishri, Muhammad Tanveer
SAGE Open
Organizational and Employee Performance
article

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

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

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.

SAGE OpenVol. 15(4)
Princess Nourah bint Abdulrahman University (SA), Prince Sultan University (SA), Canadian University of Dubai (AE), Imam Mohammad ibn Saud Islamic University (SA)
Openalex Percentile: Top 82%
Organizational and Employee Performance
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