Areas of benefit from smart linguistic models in accounting and auditing (ChatGPT as an example): Exploratory research

Authors

  • Mohamed K. Al-Gnbri Department of Accounting, Tripoli College of Science and Technology, Tripoli, Libya
  • Zakaria A. Al-Maried قسم المحاسبة، جامعة طرابلس الأهلية، طرابلس، ليبيا
  • Hanibal A. Sweed3 قسم المحاسبة، جامعة طرابلس الأهلية، طرابلس، ليبيا

DOI:

https://doi.org/10.56967/ejfb2024434

Keywords:

Generative Artificial Intelligence, ChatGPT, Accounting, Auditing, Intelligent Linguistic Models

Abstract

The research aimed to identify areas of benefit from smart linguistic models (ChatGPT as a model) in accounting and auditing. The research used the descriptive approach to describe areas of benefit. Data was collected from ChatGPT, where a set of questions were asked and analyzed by topic. The research concluded with a set of results, most notably that the areas in which ChatGPT is greatly beneficial in accounting and auditing in general are: assistance in data entry and accounting guidance, assistance in preparing reports and budgets and setting estimates, research into international accounting standards, legislation and laws, analysis and interpretation of data, assistance In planning the audit process, organizing working papers, researching international standards for external and internal auditing. As for the areas in which ChatGPT does not provide significant added value in accounting and auditing, they are when the cases are complex, complex, and have many details, and require knowledge of the legislation and laws in a specific sector or country, or when the cases require an in-depth assessment of risks or analysis of large-scale data. Evaluating the internal control of a particular company.

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Published

2024-08-25

How to Cite

Al-Gnbri م., Al-Maried ز., & Sweed ه. (2024). Areas of benefit from smart linguistic models in accounting and auditing (ChatGPT as an example): Exploratory research. Entrepreneurship Journal for Finance and Business, 5(3), 31–48. https://doi.org/10.56967/ejfb2024434

Issue

Section

Research articles

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