Artificial Intelligence Adoption in Financial Reporting: Evidence from a Technology Acceptance Model among Islamic Higher Education Students - Sinta Ardhillatul Jannah; Yusnawati Yusnawati (Journal of Economics and Management Scienties, 2026)
The adoption of artificial intelligence in financial reporting is increasingly important as accounting practices move toward automation, data-driven analysis, and digital decision-making. This study aims to analyze the factors influencing users’ intention to adopt artificial intelligence in financial reporting using the Technology Acceptance Model. A quantitative explanatory approach was applied, involving 93 students from state Islamic higher education institutions with academic experience in accounting, finance, financial reporting, or digital technology. Data were collected through a structured questionnaire using a five-point Likert scale and analyzed with Partial Least Squares Structural Equation Modeling. The measurement model showed adequate reliability and convergent validity, although the cross-loading results indicated potential conceptual overlap among several constructs. The structural model revealed that perceived ease of use had a positive and significant effect on attitude toward using and behavioral intention to use artificial intelligence. Perceived usefulness positively affected attitude but had a negative and significant effect on behavioral intention. Meanwhile, attitude toward using did not significantly affect behavioral intention and did not mediate the relationship between perceived usefulness, perceived ease of use, and intention to use artificial intelligence. These findings indicate that AI adoption in financial reporting is shaped more by direct perceptions of ease and practical usefulness than by user attitude alone. The study implies the need to strengthen AI literacy, technical readiness, and ethical awareness in financial reporting practices.