Factors Affecting Artificial Intelligence Technology Adoption Among Small and Medium Enterprises in Samphanthawong District, Bangkok

This study investigates the factors influencing the adoption of artificial intelligence (AI) technology among small and medium-sized enterprises (SMEs) in Samphanthawong District, Bangkok - a historic commercial area undergoing digital transition. The research employs a quantitative design using survey data from 321 SME entrepreneurs, drawing upon the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), and System Quality Theory. Key variables include perceived usefulness, perceived ease of use, social influence, technological experience, system quality, and organizational support. We applied hierarchical multiple regression and moderation analysis to test the direct and interaction effects. Results reveal that system quality, ease of use, and technological experience are strong predictors of AI adoption intention. Perceived usefulness becomes significant only when moderated by prior technological experience, highlighting its declining relevance among digitally mature users. Social influence was non-significant, suggesting autonomous decision-making among SME owners. Additionally, younger entrepreneurs exhibited higher AI training demands, particularly in automation and foundational skills. The findings point out that it takes intuitive AI platforms, age-sensitive training programs, and targeted policy interventions to foster inclusive digital transformation among urban SMEs.