The Impact of Artificial Intelligence on Accounting Information Systems in Jordanian Banks: An Exploratory Study

Artificial intelligence (AI) has become one of the critical technological tools for enhancing the efficiency and quality of accounting operations, minimising human errors, and accelerating data analysis and decision-making processes. Thus, the purpose of the study is to explore the impact of AI on accounting information systems(AIS) within Jordanian banks. The study proposed a research model based on the related studies. A quantitative approach was employed, using a questionnaire for data collection. The sample consisted of staff from the financial services and audit departments of 15 Jordanian banks, including financial managers, internal auditors, heads of accounts, and accountants. Several statistical methods are used for data analysis, SEM  was applied for data analysis using smartpls tool. The study found that AI has a considerable impact on the AIS system.  In order to reap the benefits of AI, the study advises Jordanian banks to implement cutting-edge technologies based on AI and machine learning to improve accounting system performance. It is recommended that further research be conducted to get a more in-depth understanding of the variables influencing the interaction between AI and the accounting information systems of banks.

Authors

Institutions

Publication Details

Journal
Tanmiyaẗ al-rāfidayn
Published
2025-05-30
DOI
https://doi.org/10.33899/tanra.2025.157288.1462
Citations
2
Primary Topic
Islamic Finance and Banking Studies
Type
article
Field-Weighted Citation Impact
7.82
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Impact of Artificial Intelligence on Accounting Information Systems in Jordanian Banks: An Exploratory Study

Ishraq Bataineh, Maha K. A. Abuyabes, Ahmad A. T. Alshekhhossin
2 citations
Tanmiyaẗ al-rāfidayn
Islamic Finance and Banking Studies
7.82
article

The Impact of Artificial Intelligence on Accounting Information Systems in Jordanian Banks: An Exploratory Study

Ishraq Bataineh, Maha K. A. Abuyabes, Ahmad A. T. Alshekhhossin
article en
2 citations

Abstract

Artificial intelligence (AI) has become one of the critical technological tools for enhancing the efficiency and quality of accounting operations, minimising human errors, and accelerating data analysis and decision-making processes. Thus, the purpose of the study is to explore the impact of AI on accounting information systems(AIS) within Jordanian banks. The study proposed a research model based on the related studies. A quantitative approach was employed, using a questionnaire for data collection. The sample consisted of staff from the financial services and audit departments of 15 Jordanian banks, including financial managers, internal auditors, heads of accounts, and accountants. Several statistical methods are used for data analysis, SEM  was applied for data analysis using smartpls tool. The study found that AI has a considerable impact on the AIS system.  In order to reap the benefits of AI, the study advises Jordanian banks to implement cutting-edge technologies based on AI and machine learning to improve accounting system performance. It is recommended that further research be conducted to get a more in-depth understanding of the variables influencing the interaction between AI and the accounting information systems of banks.

Tanmiyaẗ al-rāfidaynVol. 44(146)
Portland Cement Association (US), Northern University of Malaysia (MY)
Decent work and economic growth
Openalex Percentile: Top 3%
Islamic Finance and Banking Studies
7.82
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.