Accountant Competencies Influencing Work Performance in Artificial Intelligence Systems - Muangdech, Pawinee; Keawkasetkon, Phinit (MBA-KKU Journal, 2026)
This research aims to: 1) examine personal factors affecting work performance in the Artificial Intelligence (AI) era, and 2) investigate the accountant competency factors affecting work efficiency in the AI era. This study employed a survey research design. The sample consisted of 400 accountants working in private organizations. Data were collected using a questionnaire with a reliability coefficient of 0.79. The data were analyzed using frequency, percentage, mean, standard deviation, one-way analysis of variance (ANOVA), and multiple regression analysis. The findings revealed that accountants working in private organizations with different genders and ages demonstrated significantly different levels of work performance in AI systems at the .01 significance level. Furthermore, accountant competency factors jointly explained 84.7% of the variance in work performance in AI systems (Adjusted R² = .847). The results indicated that the competency factors of accountants, including 1) adaptability to change, 2) AI technology learning capability, 3) knowledge, and 4) attitude, had a positive influence on overall work performance in AI systems, with statistical significance at the .01 and .05 levels.