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artificial intelligence to 2030 encourages the deployment of AI across multiple sectors,
including finance (Government of Vietnam, 2021). At the same time, the accounting &
auditing strategy to 2030 emphasizes the modernization of the system and the
improvement of financial information quality (Government of Vietnam, 2022), while the
roadmap for the adoption of International Financial Reporting Standards (IFRS) in
Vietnam sets out a pathway toward convergence with IFRS (Ministry of Finance, 2020).
The convergence of digital transformation initiatives, AI development policies, and
accounting - auditing reforms has created a new policy space in which AI can be
considered a supporting instrument for the modernization of accounting & auditing
practices in Vietnam. AI has begun to be integrated into several operational processes,
such as document automation, reconciliation, and data analytics. However, the level of
adoption remains uneven and largely depends on organizational scale, data quality, and
digital infrastructure. Most current discussions in Vietnam emphasize the technological
efficiency gains of AI, while the shifts in professional competency requirements and the
governance implications arising from AI integration have not yet been fully examined.
This gap highlights the need for a systematic analysis of AI applications in the accounting
& auditing sector in Vietnam, with particular attention to the evolving competency
requirements for professionals and the formulation of policy directions that align with the
country’s institutional context.
2. AI adoption in accounting and auditing: literature review
2.1. The impact of AI on the efficiency and quality of accounting and auditing work
Recent studies have increasingly examined how AI contributes to improving the
efficiency and quality of accounting & auditing activities. Ali et al. (2023) argue that AI has
accelerated the transition from manual record keeping to digitalized systems, enabling
tasks to be performed with greater accuracy and efficiency, thereby improving reporting
quality and supporting decision-making. From a strategic perspective, Abdulameer et al.
(2022) suggest that the application of AI may open a new stage of development based on
innovation and technological advancement in the accounting field. However, the authors
also emphasize that this potential can only be realized when the technology is
implemented within appropriate control and governance frameworks. In a similar vein,
Dalwai et al. (2022) argue that AI is reshaping auditing practices through process
automation and enhanced data analytics, thereby supporting auditors’ decision-making
processes, while remaining complementary rather than substitutive to human
professionals.
Building on these perspectives, recent empirical evidence provides further insights
into how AI affects audit processes and outcomes. Fedyk et al. (2022) examine the use of
machine learning in auditing and explore its implications for audit processes. The findings
indicate that investment in AI is associated with improvements in audit quality and
reductions in audit fees. At the same time, AI gradually reduces the demand for
traditional auditors, although its impact on labor becomes evident only over time. These
quantitative results are supported by evidence from interviews, which show that AI is
typically developed as a centralized function within firms, is widely used in audit activities,
and is primarily intended to enhance audit quality, alongside improving efficiency.
More recent evidence by Rahman et al. (2024) analyzes the adoption of artificial
intelligence by audit firms and their clients. The findings show that the effects of AI
adoption on audit outcomes depend on how it is used across firms and clients. When AI is
applied jointly, it is associated with shorter audit reporting time and improved efficiency,

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