The audit profession currently faces challenges in talent scarcity and increasing transaction volumes combined with the intensive nature of manual substantive procedures. This study aims to explore the challenges in manual vouching procedures, test the efficiency of the developed AI-powered vouching tool’s performance and to explore auditors’ perception in AI technology integrated in the audit process. The tool developed in this study was designed to automate the vouching method. It incorporates human-in-the-loop concept in the design logic to maintain professional oversight.The researchers adopted a mixed-method approach which consists of semi-structured interviews to capture lived experiences of auditors and a comparative time-and-motion study to quantify efficiency gains in utilizing the AI-powered vouching tool. A post-manual vouching feedback survey was obtained from the participants who performed the manual vouching to gather insights on user experience. The results revealed a 92% improvement in processing time, reducing the average manual vouching time from 264.25 minutes (manual) to just 22 minutes (AI-assisted) across datasets. Furthermore, manual vouching resulted in 50% exception detection rate and 75 data input errors. Meanwhile, the AI tool achieved 100% exception detection rate with zero data input errors. The qualitative insights gathered from post-manual vouching survey highlight the cognitive fatigue experienced by the auditors and how volume and complexity introduced nuances in the manual process and user experience. The AI-powered vouching tool bridged these gaps by demonstrating operational consistency across different runs.This study demonstrates that the AI-powered tool can accelerate audit tasks and transform the vouching process from labor-intensive and judgment-heavy efforts into deterministic, standardized workflows. The research contributes a framework for a transaction-level AI adoption in external audit by emphasizing that the developed technology serves to augment, rather than replace, the auditor’s capabilities.
Japson et al. (Wed,) studied this question.