Unveiling Insights: A Comprehensive Bibliometric Analysis of Generative Artificial Intelligence - Lithesh, G.; Naga Sai, N. V. Y.; Sai Teja, T.; Purna Prakash, K.; Pavan Kumar, Y. V.; Ravindranath, K.; Pradeep Reddy, G. (Engineering Access, 2025)
Generative artificial intelligence (GAI) has become prominent in recent days. It has changed the facets of artificial intelligence and is widely implemented in various fields. GAI and its applications have a great influence on society. Hence, to understand its importance and influence well, a comprehensive bibliometric analysis of GAI is proposed in this paper. This bibliometric analysis aims to explore the bibliometric data in terms of challenges, proposed methods, applications, and insights. Further, it is a quantitative tool for evaluating scholarly publications. The proposed bibliometric analysis is performed on the bibliometric data collected from the Scopus (753 records) and Web of Science (400 records) databases ranging from 2013 to 2024 and 448 unique records are considered for the analysis. Further, after scrutiny of these records, 46 records are considered to discuss various applications of GAI. The proposed review is executed systematically by using the PRISMA model. To conduct the analysis, ten critical research questions are identified, and the answers are obtained through the results of the proposed analysis. The key results of this bibliometric analysis unveil various insights into GAI research in terms of impactful applications (22), patterns, research trends, the progress of GAI over the years, scholarly articles production, trending topics, acknowledged collaborative dynamics of authors, affiliations, and countries (10), top influencing authors (10), affiliations (10), and sources (10). These insights drive future aspiring researchers to understand the significance of GAI in various applications and enable them to carry out fruitful research.