This paper aims to explore external auditors’ perception of the use of artificial intelligence (AI) in the United Arab Emirates (UAE). It investigates whether there is a perception among external auditors toward the contribution of AI to audit quality. It also aims to test whether the perception of AI usage and its impact on audit quality differs between local and international external auditors. Data were collected using an online survey from 22 local and 41 international audit firms to achieve these research objectives. Participants were either the auditing manager, audit partners, senior auditors or other personnel who may have experience in the field of accounting and auditing. To test our hypotheses, data analysis was undertaken using reliability and validity tests, descriptive analysis and independent samples t-test. We found that the analysis shows that there is a non-significant difference in the perceived contribution of AI to audit quality between local and international audit firms. All the audit firms, whether local or international, have equal perceived contributions with regard to the audit quality.
Research Question: Do external auditors in the United Arab Emirates (UAE) perceive the ease of use and usefulness of Machine Learning (ML)? Motivation: This study aims to investigate external auditors' perceptions of the ease of use and usefulness of Machine Learning in auditing in the UAE. In addition, the study intends to examine the difference in perceived ease of use of Machine Learning between local and international audit companies in the UAE. Data: Data for this study were gathered from 63 external auditors working for local and global audit firms in the UAE. The study's population comprises external auditors from national and international audit companies in UAE. Tool: The questionnaire was deployed through an online survey tool. Findings: The results have shown that the findings do not support the idea that there is a different perception of the Perceived Ease of Use of Machine Learning in auditing between local and international audit firms. According to the conclusions of this study, external auditors have a restricted perception of the simplicity of use and utility of Machine Learning. Practical implications: The importance of the findings of such research stems from the lack of research evidence on the perceived ease of use and usefulness of Machine Learning in external auditing in the UAE. As a result, this paper provides new empirical evidence by assessing external auditors' assessments of the usage of Machine Learning in the UAE.
The role of internal auditing has received significant attention from researchers in the recent past. Due to its enormous contribution to the banking system, it has been used extensively to support other governance processes. The objective of this research paper is to explore how internal audit activity plays a role in the acquisition of external audit services in the national banks of the United Arab Emirates (UAE). Internal audit activity and external audit services represent a dynamic process of the corporate governance process. The study uses both qualitative and quantitative data to determine the role that internal auditing plays in the acquisition of external audits. The data is collected from 27 national banks in the UAE using questionnaires, hence it gives the opinions that people have about auditing as well as the figures of respondents. The study aimed to understand how the functions of internal audits contribute to the acquisition of external audits. The main contribution of this study is supporting the arguments that auditing researchers have not been fully responsive to the issues associated with changes in internal audit, services that may be offered, and internal audit’s growing function (Hayek, 2013)
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