Empowering SMEs with AI: From Data to Dynamic Efficiency in Information System

The growing integration of Artificial Intelligence (AI) across various sectors and facets of life is the primary inspiration for this research. In response to competitive demands, small and medium-sized enterprises (SMEs) are increasingly driven to improve operational efficiency and productivity. This study explores how key factors—such as perceived relative advantage, organizational support, compatibility, and competitive pressure—influence SMEs’ adoption of AI and overall performance. The research employs the Structural Equation Model (SEM), a robust statistical tool, to assess these relationships. Partial Least Squares (PLS) methods were utilized to test the proposed hypotheses, and purposive sampling was conducted to ensure relevant data collection. The study focuses on the JABODETABEK region in Indonesia, gathering responses from 120 SME owners or managers. Data collection took place on May 27, 2024. The findings reveal that four of the six hypotheses significantly affect AI adoption. At the same time, two have a more limited impact, offering valuable insights into the factors driving AI integration in SMEs.

Keywords—Artificial intelligence, SME performance, information systems, efficiency, transforming