Artificial Intelligence Adoption in Smaller Audit Practices

  • Mohd Syazwan Karim Universiti Teknologi MARA, Melaka
  • Nur Farahah Mohd Pauzi Universiti Teknologi MARA, Melaka
  • Adriana Shamsudin Universiti Teknologi MARA, Melaka
  • Siti Nurulhuda Mamat Universiti Teknologi MARA, Melaka
  • Muhammad Mukhlis Abdul Fatah Universiti Teknologi MARA, Melaka
  • Khairiah Ahmad Universiti Teknologi MARA, Melaka
  • Nurfarahin Roslan Universiti Teknologi MARA, Melaka
Keywords: Artificial Intelligence (AI), Auditing, Audit firms, Automation, Technology adoption

Abstract

The emergence of new technologies, such as Artificial Intelligence (AI), is anticipated to profoundly
impact the accounting and auditing sectors. AI is essential for automating repetitive tasks and enhancing audit
judgment. This study seeks to investigate the adoption of AI in small audit firms in Malaysia. A qualitative
research design was employed, involving semi-structured interviews with nine audit supervisors from small
audit firms in Kuala Lumpur, Negeri Sembilan, Pahang, and Melaka. The discussion focuses on two elements:
(1) Perceived Usefulness (PU) – emphasizing how AI enhances audit efficiency and accuracy, and (2) Perceived
Ease of Use (PEU) – highlighting the ease of adoption and integration of AI tools into existing audit workflows.
The findings reveal that AI is perceived as a valuable tool in small audit firms, improving audit quality and
workflow by significantly accelerating the audit process. However, human expertise is still required for certain
complex tasks and decision-making. Hence, it is crucial to communicate the AI’s capabilities and constraints to
prevent users from experiencing undue disappointment. The findings of this study aim to assist regulators and
standard-setters in developing guidelines, principles, and frameworks for AI adoption among audit firms in
Malaysia.

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Published
2025-03-29
How to Cite
Karim, M. S., Mohd Pauzi, N. F., Shamsudin, A., Mamat, S. N., Abdul Fatah, M. M., Ahmad, K., & Roslan, N. (2025). Artificial Intelligence Adoption in Smaller Audit Practices. Information Management and Business Review, 17(1(I)S), 241-250. https://doi.org/10.22610/imbr.v17i1(I)S.4381
Section
Research Paper