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This study aimed to identify the impact of applying artificial intelligence (expert systems, automatic learning, knowledge representation, and reasoning) on the quality of accounting information in (12) Jordanian commercial banks. To achieve the objectives of the study, the descriptive analytical approach was adopted, as the study sample consisted of All employees of the Finance Department in Jordanian commercial banks. The problem of the study addressed the role of artificial intelligence in enhancing expert systems, automatic learning, and knowledge representation and reasoning through preparing a questionnaire, of which (120) electronic questionnaires were distributed to the study individuals, and (105) questionnaires were retrieved, of which (95) were A valid questionnaire for analysis, and the statistical analysis was conducted through the (SPSS) program. The study concluded that the application of artificial intelligence in Jordanian commercial banks is applied to a very high degree. The study concluded that the application of expert systems to the quality of accounting information in Jordanian commercial banks. Automatic learning can automate routine and repetitive tasks in accounting, such as data entry and classification of transactions. The study indicates that automatic learning on the quality of accounting information in Jordanian commercial banks allows predictive analytics in accounting, by learning from historical data, and machine learning models can make predictions about future financial trends and results. The study concluded that the application of knowledge representation and inference to the quality of accounting information in Jordanian commercial banks led to knowledge representation frameworks that help maintain consistency and standardization in accounting practices. The study recommended enhancing the use of systems based on artificial intelligence for data-intensive tasks, such as data entry, processing, matching, and verification. By integrating these systems seamlessly with existing accounting processes.

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Effect of Applying the Artificial Intelligence on the Quality of Accounting Information in Commercial Banks (a Field Study)

  • 章节

  • 发表日期：

    2025年

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  • Tareq Almubaydeen,
  • Riham Alkabbji,
  • Mohammad Khalil Ahmed Fleifil

摘要

This study aimed to identify the impact of applying artificial intelligence (expert systems, automatic learning, knowledge representation, and reasoning) on the quality of accounting information in (12) Jordanian commercial banks. To achieve the objectives of the study, the descriptive analytical approach was adopted, as the study sample consisted of All employees of the Finance Department in Jordanian commercial banks. The problem of the study addressed the role of artificial intelligence in enhancing expert systems, automatic learning, and knowledge representation and reasoning through preparing a questionnaire, of which (120) electronic questionnaires were distributed to the study individuals, and (105) questionnaires were retrieved, of which (95) were A valid questionnaire for analysis, and the statistical analysis was conducted through the (SPSS) program. The study concluded that the application of artificial intelligence in Jordanian commercial banks is applied to a very high degree. The study concluded that the application of expert systems to the quality of accounting information in Jordanian commercial banks. Automatic learning can automate routine and repetitive tasks in accounting, such as data entry and classification of transactions. The study indicates that automatic learning on the quality of accounting information in Jordanian commercial banks allows predictive analytics in accounting, by learning from historical data, and machine learning models can make predictions about future financial trends and results. The study concluded that the application of knowledge representation and inference to the quality of accounting information in Jordanian commercial banks led to knowledge representation frameworks that help maintain consistency and standardization in accounting practices. The study recommended enhancing the use of systems based on artificial intelligence for data-intensive tasks, such as data entry, processing, matching, and verification. By integrating these systems seamlessly with existing accounting processes.