Convergence of Digital Transformation in Accounting and Auditing Research and Training: Preliminary Survey and Solutions

Abstract

In the context of digital transformation profoundly impacting higher education, this paper explores the integration of Artificial Intelligence (AI) into accounting and auditing education and research. Through literature review and empirical survey, the study highlights key benefits of AI, including task automation, real-time data analysis, and improved training quality. At the same time, it identifies major challenges such as infrastructure limitations, digital skill gaps, and ethical concerns. Based on the findings, the paper proposes a set of comprehensive solutions, ranging from curriculum redesign and faculty development to the establishment of legal frameworks and supportive policies for effective digital transformation in the accounting and auditing sector. This study explores the integration of digital transformation, particularly Artificial Intelligence (AI), into accounting and auditing education in Vietnam, aiming to identify benefits, challenges, and propose practical solutions. An empirical survey was conducted using a questionnaire based on the Technology Acceptance Model (TAM), targeting lecturers, alumni, and experts. Data were analyzed with SPSS 20.0 through descriptive statistics. While participants recognized AI’s potential to enhance teaching quality and student employability, actual application rates remained low (AI: 8%, data analytics: 28%). Key challenges include lack of training (80%), technical support (72%), and infrastructure (64%). Strengthening digital competencies in accounting education supports labor market readiness, drives digital economy development, and enhances financial governance, contributing to sustainable economic growth. Purpose: This study explores the integration of digital transformation, particularly Artificial Intelligence (AI), into accounting and auditing education in Vietnam, aiming to identify benefits, challenges, and propose practical solutions. Method: An empirical survey was conducted using a questionnaire based on the Technology Acceptance Model (TAM), targeting lecturers, alumni, and experts. Data were analyzed with SPSS 20.0 through descriptive statistics. Result: While participants recognized AI’s potential to enhance teaching quality and student employability, actual application rates remained low (AI: 8%, data analytics: 28%). Key challenges include lack of training (80%), technical support (72%), and infrastructure (64%). Practical Implications for Economic Growth and Development: Strengthening digital competencies in accounting education supports labor market readiness, drives digital economy development, and enhances financial governance, contributing to sustainable economic growth.