TY  - JOUR
AU  - Khanh, Duong Quang 
AU  - Anh, Nguyen Thi Van 
AU  - Hoang, Manh Quan 
AU  - Kien, Nguyen Trung 
AU  - Do, Quang Hung 
PY  - 2026
TI  - Understanding Artificial Intelligence Adoption in Vietnam: An Organizational-Level Analysis
JF  - Journal of Computer Science
VL  - 22
IS  - 5
DO  - 10.3844/jcssp.2026.1636.1648
UR  - https://thescipub.com/abstract/jcssp.2026.1636.1648
AB  - This study examines the level, determinants, and perceived outcomes of Artificial Intelligence (AI) adoption in Vietnamese organizations using survey data from 142 employees and managers across multiple sectors. Descriptive statistics, t-tests, ANOVA, and multiple regression were applied to analyze sectoral differences, the role of training, and predictors of AI-enabled work performance. The results show a moderate-to-high level of AI adoption, with chatbots and Microsoft Copilot as the most widely used tools. AI is perceived to improve work performance, operational efficiency, and decision-making. However, only 32.4% of organizations provide formal AI training, indicating a gap between individual and organizational adoption. Sectoral differences are significant, with technology and finance leading in AI knowledge and usage. Regression results reveal that AI usage frequency and AI knowledge are the strongest predictors of work performance, while privacy and ethical concerns negatively affect outcomes. The findings highlight the importance of human capital, training, and governance in realizing AI-driven performance benefits in emerging economies.