This study aims to investigate the impact of artificial intelligence (AI) technologies on the quality of accounting data by evaluating improvements in accuracy, processing time, and reliability after implementing AI in accounting processes. Statistical analysis was conducted using a questionnaire distributed to 179 respondents in branches of private banks in Babylon Governorate. T-tests and analysis of variance (ANOVA) were performed to measure statistical differences between data before and after AI implementation. Multiple regression analysis was also used to examine the relationship between data quality and independent variables. The results showed a significant improvement in the quality of accounting data after AI implementation, with increased data accuracy and reliability, as well as a decrease in processing time. Regression analysis also demonstrated that processing time directly affects data reliability, with statistical significance. These results indicate that the application of AI in accounting effectively contributes to improving the quality of accounting data, reducing operational errors, and increasing financial efficiency. One of the most important findings of the research is the reduction in financial data processing time through the adoption of intelligent automation, which contributes to faster financial decision-making and enhanced regulatory compliance. The statistical model also indicates that there are other variables that may affect the quality of the data, such as the size of the data, the experience of the accountants, and the accounting regulations that govern the use of artificial intelligence.
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