Technological and Organizational Determinants of AI Integration in SME Business Analytics Systems

This paper examines the integration of Artificial Intelligence (AI) into business analytics (BA) platforms within small and medium-sized enterprises (SMEs). The study aims to identify and theoretically explain the key determinants, enablers and barriers which influence a successful AI adoption in SME. Building on the Technology-Organization-Environment (TOE) frame-work and the Resource-Based View (RBV), it develops an integrated conceptual model that links technological, organizational and environmental factors with resource-based capabilities. Methodologically, the research follows a Structured Literature Review (SLR) approach and synthesizes the insights from 124 peer-reviewed publications from Scopus. The findings re-veal that successful AI-driven BA implementation largely depends on the development of Big Data Analytics Capabilities (BDAC), management support, integration capability, data gov-ernance and an organizational learning culture. Practically, the paper provides actionable rec-ommendations for SMEs on how to strategically inetgrate AI and analytics initiatives through strong governance, leadership and continuous learning. Overall, it contributes a theory-driven framework that advances the integration of TOE and RBV perspectives and offers a founda-tion for future empirical research on AI adoption in SMEs.