Artificial intelligence applications accelerate sectoral transformation by improving customer service and optimizing operational efficiency in the banking sector. Thanks to artificial intelligence, banks gain a competitive advantage by offering personalized products to their customers, establishing more effective communication with them and automating transactions. Artificial intelligence in the banking sector is rapidly becoming widespread thanks to the potential of tools such as chatbots, voice assistants and machine learning to improve customer experience, reduce fraud and reduce costs. Banks that want to increase customer satisfaction and operational efficiency try to gain a competitive advantage by investing in artificial intelligence technologies. In this study, a comprehensive evaluation of research in this field was made by analyzing the existing scientific literature on the use of artificial intelligence in the banking sector using bibliometric methods. The study’s data set was taken from the Web of Science (WoS) database and the bibliometric analysis of the study was carried out using the R programming language. As a result of the bibliometric analysis of the subject of artificial intelligence in the banking sector applied within this framework determined that studies were carried out on this subject between 1999-2024 and a total of 362 publications were produced. Within the applied bibliometric analysis framework, it was concluded that scientific productivity was low between 1999 and 2007 that scientific productivity started to increase significantly in 2017 and that scientific productivity has accelerated considerably in recent years. It was determined that India is the leader in artificial intelligence productivity in the banking sector. In addition, the importance of the concepts of “performance,” “model” and “artificial intelligence” for researchers was emphasized. The importance of artificial intelligence was noted especially in customer experience, risk management and operational efficiency.