Artificial Intelligence Adoption Among SMEs in the UAE: Barriers, Enabling Factors, and an Evidence-Informed Framework

Abstract

Abstract Artificial intelligence (AI) is increasingly being incorporated into business activities such as marketing, customer service, analytics, forecasting, and administrative processes. Small and medium-sized enterprises (SMEs) are particularly important to the United Arab Emirates (UAE) economy, representing approximately 95% of businesses and around 86% of private-sector employment. At the same time, the UAE has developed a comparatively supportive environment for artificial intelligence through digital infrastructure, government initiatives, regulatory development, and investment in technological innovation. However, access to AI technology does not necessarily result in effective adoption. SMEs may face organizational, technological, financial, skills-related, and governance challenges when attempting to integrate AI into their operations. This study examines the technological, organizational, and environmental factors influencing effective AI adoption among UAE SMEs and considers practical strategies for addressing implementation challenges. The study uses a structured qualitative secondary research methodology, drawing primarily on UAE government publications, institutional research, and peer-reviewed academic literature. Two particularly relevant UAE sources provide empirical evidence: a 2025 Mohammed Bin Rashid School of Government study involving 81 UAE-based AI and digital SMEs, and a 2025 peer-reviewed study involving 315 respondents from UAE hospitality SMEs. The evidence indicates that AI adoption is influenced by more than technological availability. Top-management support, competitive pressure, government regulation, perceived usefulness, competitive advantage, and employee capability are significantly associated with AI adoption intention in the studied UAE hospitality SME sample. UAE ecosystem research additionally highlights advanced computing requirements, financing, AI governance, talent, compliance, and scaling challenges. Broader SME literature reinforces the importance of skills, data readiness, implementation costs, uncertainty regarding returns, and organizational capability. Based on this evidence, the study proposes an evidence-informed seven-phase framework: Define, Assess, Select, Pilot, Measure, Govern, and Scale. The framework is intended to help UAE SMEs move from initial AI experimentation toward adoption that is strategic, measurable, responsible, and scalable. Keywords: Artificial intelligence; SMEs; UAE; AI adoption; digital transformation; Technology–Organization–Environment; responsible AI