A Bibliometric Analysis of Global Research Trends in Artificial Intelligence from 2019 to 2023

Abstract

This bibliometric analysis examines global research trends in Artificial Intelligence (AI) from 2019 to 2023, using 7,030 Scopus indexed documents. The study found an annual growth rate of 25.93%, indicating a substantial increase in AI research effort. The majority of articles were created by collaborative teams, with an average of 4.28 authors per paper, with only 415 being single-authored. IEEE Access is the most prolific contributor, King Saud University is the leading institution, and China is the main publishing country, with 1,277 corresponding authors and the highest citation count (19,873). Thematic analysis highlights a strong emphasis on machine learning, deep learning, and neural networks as foundational topics, alongside growing interest in ethical AI and convolutional neural networks, signaling the field's evolution toward addressing societal challenges and specialized applications. International collaboration plays a significant role, with 31.31% of publications involving authors from multiple countries. While the volume of AI research grows, newer articles have lower average citations due to their recent publication date. These findings highlight the interdisciplinary and worldwide nature of AI research, as well as its transformational potential for academia, industry, and policymakers. By mapping major trends and contributors, this report gives significant insights into the changing AI landscape, identifying potential for improving worldwide research collaboration and addressing growing difficulties in the field.