The aim of this bibliometric analysis is to evaluate the intersection of research on AI and finance and to assess the past study publication trends based on the Web of Science (WoS) database. “Artificial Intelligence” and “Finance” were two significant phrases that were employed between 2004 and 2024 using the WoS database. 3406 published articles were collected and evaluated using a bibliometric analysis approach. The researchers examined five performance analysis indicators, including publications by prolific authors, cumulative publications, affiliations by top universities, contributions from top publishing houses, and countries. The minimum values for each indicator in the VOSviewer software were determined for data analysis. Scientific mapping was conducted on author citation, co-citation analysis, bibliographic coupling, and co-occurrence of keywords. The research identified a surge in the publications beginning in 2018 which highlighted the application of AI and finance. Most of the documents related to AI and finance were found to be articles. Out of 10,081 authors, Zhang WY was the most prolific author with 57 publications. Southwestern University of Finance Economics, China, ranked first out of 3578 universities with 259 publications. Moreover, China, the USA, and Brazil were the top three contributors to the literature. Elsevier led first with 1084 published articles. English-language publications outnumbered those in other languages. According to the keyword co-occurrence analysis, artificial intelligence and finance stood out in their occurrences, 626 and 103, respectively. The chapter provides insights into the potential implications and future prospects of AI-driven technologies. The results offer market participants, particularly fintech and finance companies, useful recommendations on how to leverage AI to enhance their decision-making.