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Artificial intelligence represents the cutting-edge frontier in influencer marketing, offering a novel approach to leveraging social media data. This study aims to provide a comprehensive analysis of the recent state and future directions of artificial intelligence-infused influencer marketing through bibliometric analysis. For substantial bibliometric analysis, the study contains 316 documents published in journals indexed in the Scopus database for the period ranging from 2004 to 2023. The yearly publications have risen from 2 in 2004 to 55 in 2023, with an average age of 19.06 years and a citation rate of 22.19 yearly. The number of publications in this domain accelerated in 2020. According to the review findings, Hong Kong is the most productive country in this research domain. The leading affiliation is Hanyang University. The top contributing author is Gatica Perez-D. The most prolific source is the AAAI Spring Symposium Technical Report. Keyword occurrence analysis highlights prevalent terms such as Blogs, Social media networking (online) and Data mining alongside emerging keywords such as Influencer marketing, User-Generated Content, Artificial Intelligence, Sentiment Analysis, and Semantic Analysis in this domain to anticipate future inclinations. Performance analysis, further delves into Collaborative efforts among countries, sources, affiliations and authors have also been done using tools like Biblioshiny and Vos Viewer. The study offers novel contributions to the existing literature in terms of comprehensively providing evidence of the current practices of AI-integrated influencer marketing.