Page 593 - ISC PROCEEDINGS 21.4

merely a matter of technological investment but is also closely linked to strengthening
professional expertise, professional judgment, and internal control mechanisms within
different types of organizations.
In policy terms, the implementation of AI in accounting & auditing should follow a
roadmap that is appropriate for the conditions of a developing economy, where
technological readiness and resources remain uneven. Rather than prioritizing the formal
adoption of technological solutions, greater attention should be given to improving data
quality, standardizing professional competency frameworks, and strengthening data
governance mechanisms. Reducing the gap between technological investment and the
capacity of professionals to effectively utilize such technology is a key condition for AI to
genuinely contribute to improving service quality and the long-term sustainability of the
accounting & auditing profession in Vietnam.
This study offers a relatively systematic overview of the current application of AI
and clarifies the issues arising for the development of professional competencies in a
digital environment. Future research may provide empirical evidence on the impact of AI
on productivity, audit quality, and evolving skill requirements within the accounting &
auditing workforce, thereby strengthening the foundation for policy formulation and
professional training in the coming period.
This study provides a structured overview of AI adoption in accounting and auditing
in Vietnam based on publicly available sources. While this approach is appropriate for
capturing broad patterns, it may not fully reflect firm-level differences in implementation
practices. In addition, the study focuses on describing current developments and their
implications for professional competencies, rather than examining their effects through
empirical testing. Future research could build on this analysis by using firm-level or survey
data to examine how AI adoption relates to audit quality, productivity, and changes in
professional roles. Comparative studies across different institutional contexts would also
help clarify how national conditions shape adoption patterns. Further work may also
explore in more detail how key competencies such as data analysis, evaluation of system
outputs, and technology governance are developed and applied in practice.

References
[1]. Abdulameer, M., Mansoor, M. M., Alchuban, M., Rashed, A., Al-Showaikh, F.,
Hamdan, A. (2022). The Impact of Artificial Intelligence (AI) on the Development of
Accounting and Auditing Profession. In: Hamdan, A., Hassanien, A.E., Mescon, T., Alareeni,
B. (eds) Technologies, Artificial Intelligence and the Future of Learning Post-COVID-19.
Studies in Computational Intelligence, vol 1019. Springer, Cham.
https://doi.org/10.1007/978-3-030-93921-2_12
[2]. Abu Afifa, M. M., Nguyen, T. H., Le, M. T. T., Nguyen, L., & Tran, T. T. H. (2025).
Accounting going digital: A Vietnamese experimental study on artificial intelligence in
accounting. VINE Journal of Information and Knowledge Management Systems, 55(4),
1031–1050. https://doi.org/10.1108/VJIKMS-10-2023-0266
[3]. Ali, S.M., Hasan, Z. J., Hamdan, A., Al-Mekhlaf, M. (2023). Artificial Intelligence
(AI) in the Education of Accounting and Auditing Profession. In: Alareeni, B., Hamdan, A.,
Khamis, R., Khoury, R.E. (eds) Digitalisation: Opportunities and Challenges for Business.
ICBT 2022. Lecture Notes in Networks and Systems, vol 621. Springer, Cham.
https://doi.org/10.1007/978-3-031-26956-1_61

592