This study examines how expert systems, neural networks, and genetic algorithms of artificial intelligence technologies accurately represent Jordanian commercial bank financial data. This paper achieved its aims using descriptive analysis. Twelve Jordanian commercial banks were selected for this investigation. The research sample includes accountants, auditors, financial analysts, and IT professionals. From this group, 280 electronic questionnaires were dispersed throughout these banks, and 250 were picked up for statistical analysis. SPSS was used to analyse data on AI and financial data integrity. These results showed that expert systems, neural networks, and evolutionary algorithms improved Jordanian commercial banks’ financial data representation statistically. The study found that Jordanian commercial banks should invest more in AI technology to improve financial accuracy and stakeholder confidence through data openness.