Digitalization and Openness as Determinants of Accounting Students’ Readiness for Ai-Based Systems
DOI:
https://doi.org/10.22219/jrak.v16i1.43149Keywords:
Accounting Education, Artificial Intelligence, Learning Digitalization, Openness, Psychological Readiness, Technology AdaptationAbstract
Objective: This study aims to analyze how digital exposure in the learning process and personality characteristics interact in shaping accounting students’ readiness to use Artificial Intelligence (AI) based accounting systems. The study integrates three main constructs digitalization of the learning environment (X1), the personality dimension of openness to experience (X2), and students’ psychological readiness (Z) into a unified structural model framework. This approach is developed to address the limitations of previous studies that generally examined these three variables separately, and therefore have not been able to comprehensively explain how digital technology exposure and individual characteristics simultaneously shape readiness to adapt to AI technology.
Methodology/Approach: This study employs a quantitative approach with an explanatory research design aimed at testing the relationships among variables within the proposed model. A total of 150 accounting students from several universities in Indonesia participated as research respondents. Data were collected through structured questionnaires and analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) method. The analysis stages included testing both the measurement model and the structural model, including indicator reliability, composite reliability, Average Variance Extracted (AVE), and discriminant validity using the Heterotrait–Monotrait Ratio (HTMT) approach. The structural model was evaluated through model fit indices such as SRMR and NFI, multicollinearity analysis using the Variance Inflation Factor (VIF), and model explanatory power through the R-square value and effect size (f²). To ensure the absence of common method bias, this study also applied the Harman single factor test and the full collinearity test. In addition, the testing of direct and indirect relationships, as well as the mediating role, was analyzed using the Variance Accounted For (VAF) calculation.
Findings: The findings indicate that students’ readiness to adopt Artificial Intelligence (AI) based accounting systems is shaped through the interaction between digital learning exposure, the level of openness to experience, and students’ psychological readiness. A digitized learning environment contributes to enhancing students’ understanding and confidence when using AI-based tools, while the openness trait encourages the development of a more constructive attitude toward technological innovation. These findings affirm that readiness for AI implementation in accounting education is not determined solely by the availability of digital infrastructure, but is also strongly influenced by students’ emotional readiness and cognitive capacity. In this context, psychological readiness plays an important role as a connecting mechanism that transforms technological experiences and personality characteristics into actual adaptive capability.
Practical Implications: This study provides recommendations for universities seeking to accelerate digital transformation in accounting education. Such efforts can be implemented through the development of AI integrated learning platforms, the optimization of Learning Management Systems (LMS), and the integration of cloud-based accounting applications into learning practices. In addition to strengthening technological infrastructure, educational institutions also need to pay attention to students’ psychological readiness, including the development of emotional regulation skills, the reduction of technology-related anxiety, and the enhancement of confidence in using AI based systems. Learning strategies should also consider students’ personality characteristics so that the process of technological adaptation can occur more effectively. Furthermore, improving lecturers’ competencies, providing AI literacy training, and establishing collaborations with industry are important steps to ensure alignment between academic competencies and technological demands in the workplace.
Originality/Value:This study offers an integrative framework that simultaneously connects the digitalization of learning, personality factors, and psychological readiness in explaining readiness to adapt to AI an area that has rarely been comprehensively examined in accounting education research. The study not only strengthens the validity of theoretical pathways derived from the UTAUT theory, Big Five Personality, and Emotional Intelligence, but also provides a conceptual contribution by emphasizing the role of partial mediation as a key mechanism in shaping AI adaptation readiness among accounting students.
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