We hypothesized in our research study here that “artificial intelligence has a statistically significant influence on the efficiency of digital finance within banking sector in Jordan.” Realizing such aim required us to adopt dimensions of AI in financial setting that including automated decision-making, predictive analytics, natural language processing (NLP), robotic process automation (RPA), blockchain, and distributed ledger technology (DLT). To reach valid results, we have adopted the quantitative methodology through a self-administered questionnaire that was distributed on 76 managers and employees within 5 Jordanian banks. SPSS was used in order to deal with collected primary data. Results of analysis indicated that acceptance of study hypothesis and it appeared that artificial intelligence has a statistically significant influence on the efficiency of digital finance within banking sector in Jordan. Among the chosen variables, it was seen that robotic process automation (RPA) was the highest in influence with r = 0.769. We recommend that banking sector in Jordan continue to invest in and integrate AI systems that automate decision-making processes. This can lead to improved operational efficiency, faster response times, and more accurate decision-making in financial transactions and customer interactions. Further recommendations were presented in the study.