Explainable artificial intelligence in auditing: Factors influencing auditors’ acceptance in Vietnam - Thanh, Le Chi; Duyen, Vu Thi Mai; Hang, Nguyen Thi Thanh (Edelweiss Applied Science and Technology, 2025)
Amid rapid digital transformation, this study examines factors influencing auditors’ acceptance of explainable artificial intelligence (XAI) in Vietnam. Drawing on the Technology Acceptance Model and XAI literature, a structured questionnaire was administered to auditors at Vietnamese audit firms, yielding 350 valid responses. The data were analyzed using reliability tests, exploratory factor analysis, and multiple linear regression in SPSS. The results show that perceived usefulness, perceived ease of use, perceived transparency and security, and organizational support all have positive and statistically significant impacts on auditors’ behavioral intention to use XAI, with transparency and security exerting the strongest effect. These findings confirm that explainability, traceability, and reliability are core conditions for AI adoption in a highly regulated, trust-based profession. The study extends technology acceptance research to the context of XAI-enabled auditing in an emerging market and highlights several managerial implications for audit firms and regulators, including prioritizing explainability-by-design, investing in training and user-friendly systems, and aligning digital transformation strategies and governance frameworks with responsible XAI deployment.