Generative AI in Internal Audit: An Exploration of Visualization Applications

DOI: https://doi.org/10.62517/jse.202611103

Author(s)

Qiong Lei

Affiliation(s)

School of Business, Guilin Normal University, Guilin, Guangxi, China

Abstract

The rapid advancement of information technology and the exponential growth of enterprise data have posed unprecedented challenges to traditional internal audit methods. Against this backdrop, with its powerful capabilities in content generation and interaction, Generative Artificial Intelligence (AIGC) presents new development opportunities for the field of internal audit. This paper focuses on the visualization applications of Generative Artificial Intelligence (AIGC) in internal audit, aiming to conduct an in-depth exploration of this subject. It begins by briefly outlining the technical characteristics of AIGC and its current application status in the auditing domain. Subsequently, the article the various potential issues arising from the application of AIGC in internal audit. And finally proposes effective strategies to address these challenges. This study not only offers theoretical references and practical insights for promoting the deepened application of AIGC visualization in internal audit, but also contributes to enhancing the quality and value of audit practices, thereby laying a research foundation for the realization of intelligent audit.

Keywords

AIGC; Internal Audit; Visualization; Intelligent Audit

References

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