Determinants of AI Adoption and How the Adoption Affects the Business Performance of Small and Medium-Scale Enterprises
Background: Despite the revolutionary potential of artificial intelligence, small and medium-scale enterprises in Vietnam are hesitant to embrace it due to a lack of resources, inaccurate data, and inadequate infrastructure. This research examines the key facilitators of performance enhancement enabled by artificial intelligence. Objective: This study aims to understand the variables that influence AI adoption among Vietnam's small and medium enterprises and how such adoption impacts business performance. Methodology: This study employs a mixed-methods research strategy, combining quantitative validation with qualitative insights gathered from focus groups and structural equation modelling. There were responses to the survey, but 885 legitimate responses were gathered from five southern Vietnamese provinces. Result: According to the results, the factors that have the most significant impact on artificial intelligence adoption and business performance are data quality and availability, followed by organisational culture, external factors, and internal factors. Artificial intelligence serves as the intermediary for transforming these factors into improved business performance. Conclusion: When paired with high-quality data, an innovation-driven culture, and enabling internal and external conditions, this study demonstrates that artificial intelligence significantly enhances the performance of SMEs. Unique Contribution: The research contributes to the existing literature on technology adoption by presenting a comprehensive model and offering practical recommendations to policymakers and managers of small and medium-sized enterprises. Key Recommendation: Small and medium enterprises in Vietnam should emphasise establishing strong data infrastructure and governance processes to improve their company performance with artificial intelligence. Successful artificial intelligence adoption is driven by high-quality, accessible, and well-managed data, which enhances operational efficiency and strategic decision-making.
Authors
- Huỳnh Cao Tuấn
- Nguyen Thanh Tung
Institutions
- Lac Hong University (VN)
Publication Details
- Journal
- SHILAP Revista de lepidopterología
- Published
- 2026-01-01
- Primary Topic
- AI in Service Interactions
- Type
- article
- Field-Weighted Citation Impact
- 0.00