Aim: The aim of this paper is to analyse research trends on the use of artificial intelligence in the automotive industry, with a focus on geographical distribution, key publication sources and thematic changes over time. Methodology: A systematic bibliometric analysis was conducted using the Bibliometrix tool in R, covering publications from 2013-2023 available in the Scopus database. This approach enabled a quantitative assessment of research trends, the geography of the most influential authors and thematic changes in scientific publications. Results: The analysis reveals a significant shift in research focus from basic information science and computer simulation to advanced applications of AI, particularly in autonomous vehicles and machine learning methods. There is a notable concentration of research efforts in developed countries with strong automotive and technological sectors, such as the United States, China, Germany, and India. Implications and recommendations: The findings suggest a need for further research addressing the practical challenges of implementing AI in real-world automotive environments. Future studies should focus on evaluating the long-term effects of AI on vehicle performance, safety, and user experience. Additionally, expanding research beyond leading technological regions could provide a more comprehensive understanding of global trends and challenges. Originality/value: This research provides a novel bibliometric perspective on the integration of AI in the automotive industry, offering valuable insights into current research trends and identifying significant gaps in the literature. By highlighting the geographical concentration of research and the shift towards advanced AI applications, this study contributes to a deeper understanding of how AI is shaping the future of automotive technology.
Greńczuk et al. (Mon,) studied this question.
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