<![CDATA[Artificial intelligence (AI) is becoming increasingly accessible to small and medium-sized enterprises (SMEs) through cloud platforms, generative AI, machine learning services, intelligent automation, and AI-enabled business applications. Yet technology availability does not guarantee organizational adoption or measurable business value. This study develops an integrative Technology–Organization–Environment (TOE) framework explaining how SMEs can convert AI adoption into operational efficiency and business performance. The study uses an integrative literature review combining foundational technology-adoption theory with recent peer-reviewed research on AI adoption and use in SMEs. The synthesis identifies five technological determinants—relative advantage, compatibility, technological readiness, data readiness, and security/integration; four organizational determinants—top management support, AI and digital capability, financial resources, and data-driven culture; and four environmental determinants—competitive pressure, customer demand, external ecosystem support, and policy/institutional support. The findings indicate that AI creates value not through adoption alone but through integration into business processes such as automation, analytics, prediction, personalization, and decision support. Organizational capability emerges as a critical conversion mechanism linking technological potential to performance outcomes. The study further argues that responsible AI governance, including human oversight, privacy protection, cybersecurity, transparency, and accountability, should be treated as a cross-cutting implementation condition. The resulting framework contributes to the SME digital-transformation literature by linking adoption antecedents with value-realization mechanisms and provides a practical roadmap for phased AI implementation in resource-constrained firms. Keywords: artificial intelligence; SMEs; technology adoption; TOE framework; operational efficiency; business performance]]>
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