Ai-Enhanced Audit Inquiry: A Research Note
Keywords
Artificial intelligence; Audit inquiry; Continuous auditing; Markov models
Abstract
Artificial intelligence (AI) and machine learning (ML) are transforming organizations and will soon transform auditing. Many promising areas of AI and ML are within the continuous auditing context. However, the field has yet to recognize how AI and ML can be used for audit inquiry, an essential feature of both traditional audits and continuous auditing. In this research note, we discuss the potential viability of AI-enhanced audit inquiry using ‘‘bots’’ that automatically generate audit inquiries as well as evaluate client responses. In addition, we discuss opportunities for future research in this specific area of automated auditing.
Publication Date
9-1-2018
Publication Title
Journal of Emerging Technologies in Accounting
Volume
15
Issue
2
Number of Pages
111-116
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.2308/jeta-52310
Copyright Status
Unknown
Socpus ID
85070769716 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85070769716
STARS Citation
Raschke, Robyn L.; Saiewitz, Aaron; Kachroo, Pushkin; and Lennard, Jacob B., "Ai-Enhanced Audit Inquiry: A Research Note" (2018). Scopus Export 2015-2019. 8545.
https://stars.library.ucf.edu/scopus2015/8545