Impact of AI on Self-learning Capabilities of Employees in SMEs

This study investigates the impact of Artificial Intelligence (AI) on self-directed learning and critical thinking among employees in Small and Medium Enterprises (SMEs) in Ho Chi Minh City, Vietnam. A mixed-methods research approach was employed, combining a quantitative survey of 305 employees across various industries and qualitative data from 15 in-depth interviews with managers and staff. Structural Equation Modeling (SEM) was used to analyze the relationships between AI access, employee attitudes, organizational support, digital literacy, and self-learning outcomes. Qualitative analysis provided additional insights into contextual factors influencing AI adoption. The findings highlight that AI significantly enhances self-directed learning when SMEs offer structured training programs and technological resources. Employees with strong critical thinking skills effectively utilize AI tools for evidence-based decision-making and analytical tasks. However, barriers such as disparities in digital literacy, inconsistent AI adoption strategies, and insufficient organizational support hinder optimal outcomes. Organizational support emerged as a key enabler, with employees receiving adequate training reporting improved learning and skill development. This study extends the Self-Directed Learning Theory (SDL) and Technology Acceptance Model (TAM) by identifying mediating roles of organizational and individual factors. Practical recommendations include fostering digital literacy, critical thinking, and AI-supportive organizational cultures to optimize workforce development.