Generative artificial intelligence (GAI) has significantly disrupted the educational landscape, ushering in profound transformation. In this comprehensive research study, global databases such as Scopus and Web of Science (WoS) were meticulously curated for data collection within the publication years of the last five years, i.e., 2019–2023. The search criteria involved a thorough exploration of documents featuring “Generative Artificial Intelligence” and “education” in the article title, abstract, and keywords, assembling a refined dataset comprising 116 publications. The study design incorporated the widely recognized PRISMA and PICOC frameworks to ensure methodological rigor. Data analysis was conducted utilizing the advanced VOSviewer_1.6.20 software. The investigation delved into diverse aspects of citation patterns, revealing notable variations across sources, authors, and organizations. The research showcased a transdisciplinary nature by employing bibliographic coupling across multiple countries and co-citation among cited sources and authors. Incorporating PICOC components facilitated a critical analysis of the research problem, relating it to policy and practical considerations while identifying prevailing trends in current research. Consequently, the study provides insights into the potential impact on practices and policies and lays the groundwork for future lines of inquiry in the realm of GAI in education.