Future auditing: Machine learning's impact on audit capacity stress - young auditors' perceptions using UTAUT

Eugenia Carisa (), Evelyn Nadia Tedjosugondo () and Armanto Witjaksono ()

Edelweiss Applied Science and Technology, 2024, vol. 8, issue 6, 4427-4446

Abstract: Advancing technologies have potential to revolutionize the future of auditing. This study investigates the impact of machine learning adoption on audit capacity stress among Indonesian external auditors. A survey approach was used to collect data from 100 auditors working in public accounting firms. The Unified Theory of Acceptance and Use of Technology (UTAUT) model was employed to assess factors influencing auditors' perceptions of machine learning usage. The result that comprises of young auditors to be the most respondents show performance expectancy, effort expectancy, and social influence are insignificant towards audit capacity stress. However, facilitating conditions were found to have a significant impact on audit capacity stress, suggesting that infrastructure and resource availability are crucial for young auditors' acceptance of machine learning and its audit capacity stress-reducing effects. Thus, Indonesian auditor requires additional facilitating support to alleviate audit capacity stress. These findings contribute to the understanding of technology adoption and audit capacity stress in the evolving future audit profession.

Keywords: Audit capacity stress; Auditor perception; Future auditing; Machine learning; UTAUT model. (search for similar items in EconPapers)
Date: 2024
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