Explaining Tax Digitalization Adoption: The Mediating Role of Digital Literacy in the Effects of AI-Driven Automation, Effort Expectancy, and Facilitating Conditions - Della Fadhilatunisa; M. Miftach Fakhri; Aprilianti Nirmalasari; Andi Dio Nurul Awalia; Soeharto Soeharto (Journal of Economic Education and Entrepreneurship Studies, 2025)
The acceleration of tax digitalization through artificial intelligence (AI) has redefined modern taxation systems; however, its success largely depends on users’ digital literacy and readiness to embrace automation. This study investigates the mediating role of digital literacy in the relationship between AI-driven automation, facilitating conditions, and effort expectancy on tax digitalization adoption in Indonesia. Employing a quantitative approach with a cross-sectional survey design, data were collected from 161 individual and professional taxpayers using purposive sampling methods. The analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results demonstrate that digital literacy exerts the strongest direct and significant influence on the adoption of tax digitalization. It also mediates the effects of AI-driven automation and facilitating conditions, whereas effort expectancy shows a positive but statistically insignificant relationship. These findings underscore that digital literacy is not merely a supporting factor but a fundamental determinant of successful digital tax transformations. This study implies that policies aimed at promoting tax digitalization should prioritize digital literacy enhancement through systematic education, technical training, and user-friendly system design. By strengthening digital competence, tax authorities can increase user engagement, improve compliance, and facilitate an equitable digital transformation within tax administration.