Overview of AI-powered predictive analytics in audits: Perspective evidence from Kuwait auditors

This paper aims to analyze the capability of advanced AI as a predictor of audit quality with particular reference to auditors in Kuwait. The research focuses on understanding the role of advanced AI technologies in the improvement of most audit activities around risk, fraud, and compliance. In...

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Main Author: Awwad Alnesafi
Format: Article
Language:English
Published: Growing Science 2025-01-01
Series:International Journal of Data and Network Science
Online Access:https://www.growingscience.com/ijds/Vol9/ijdns_2025_7.pdf
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author Awwad Alnesafi
author_facet Awwad Alnesafi
author_sort Awwad Alnesafi
collection DOAJ
description This paper aims to analyze the capability of advanced AI as a predictor of audit quality with particular reference to auditors in Kuwait. The research focuses on understanding the role of advanced AI technologies in the improvement of most audit activities around risk, fraud, and compliance. In order to classify the Kuwaiti auditors into different segments on the basis of their internet usage, both the quantitative data collected through a questionnaire survey is used with additional data collected from structured interviews with them. The results are expected to offer a rich and detailed account of the pragmatic opportunities and difficulties of applying AI in audits while highlighting its potential of reshaping conventional approaches. This study contributes relevant knowledge regarding the audit quality and governance garnered from linking theory and practice, providing the feasible recommendations for auditors and policymakers in the member countries of the GCC.
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record_format Article
series International Journal of Data and Network Science
spelling doaj-art-e0e42087bdbd430f958ea895ae3c89f42025-08-20T03:24:43ZengGrowing ScienceInternational Journal of Data and Network Science2561-81482561-81562025-01-019339541010.5267/j.ijdns.2025.4.001Overview of AI-powered predictive analytics in audits: Perspective evidence from Kuwait auditorsAwwad Alnesafi This paper aims to analyze the capability of advanced AI as a predictor of audit quality with particular reference to auditors in Kuwait. The research focuses on understanding the role of advanced AI technologies in the improvement of most audit activities around risk, fraud, and compliance. In order to classify the Kuwaiti auditors into different segments on the basis of their internet usage, both the quantitative data collected through a questionnaire survey is used with additional data collected from structured interviews with them. The results are expected to offer a rich and detailed account of the pragmatic opportunities and difficulties of applying AI in audits while highlighting its potential of reshaping conventional approaches. This study contributes relevant knowledge regarding the audit quality and governance garnered from linking theory and practice, providing the feasible recommendations for auditors and policymakers in the member countries of the GCC.https://www.growingscience.com/ijds/Vol9/ijdns_2025_7.pdf
spellingShingle Awwad Alnesafi
Overview of AI-powered predictive analytics in audits: Perspective evidence from Kuwait auditors
International Journal of Data and Network Science
title Overview of AI-powered predictive analytics in audits: Perspective evidence from Kuwait auditors
title_full Overview of AI-powered predictive analytics in audits: Perspective evidence from Kuwait auditors
title_fullStr Overview of AI-powered predictive analytics in audits: Perspective evidence from Kuwait auditors
title_full_unstemmed Overview of AI-powered predictive analytics in audits: Perspective evidence from Kuwait auditors
title_short Overview of AI-powered predictive analytics in audits: Perspective evidence from Kuwait auditors
title_sort overview of ai powered predictive analytics in audits perspective evidence from kuwait auditors
url https://www.growingscience.com/ijds/Vol9/ijdns_2025_7.pdf
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