Abstract: Artificial Intelligence (AI) is transforming the automotive industry by enabling smart manufacturing, optimizing supply chains, enhancing vehicle safety, and accelerating the shift toward autonomous mobility. This bibliometric study provides a systematic overview of the intellectual landscape of AI adoption in the automotive sector. Using data from Scopus, Web of Science, and OpenAlex, we analyze publication trends, influential authors, key institutions, thematic clusters, and international collaboration networks. Findings show a sharp rise in research output during the last decade, with major themes including predictive maintenance, computer vision for quality control, autonomous driving systems, supply chain optimization, and sustainable manufacturing. Emerging areas such as explainable AI, digital twins, and AI-enabled Industry 4.0 architectures are gaining increasing visibility. Collaboration analysis highlights strong contributions from Asia, Europe, and North America, with growing interdisciplinary networks bridging engineering, computer science, and management. This work not only maps the state of research but also identifies gaps and future directions for advancing AI adoption in the automotive industry. The study offers practical insights for researchers, industry practitioners, and policymakers aiming to harness AI for operational efficiency, competitiveness, and sustainable growth.

Sara OULED LAGHZAL and EL OUADI Abdelmajid. “Mapping Artificial Intelligence Research in Automotive Manufacturing: A Bibliometric Study”. International Journal of Advanced Computer Science and Applications (IJACSA) 16.11 (2025). http://dx.doi.org/10.14569/IJACSA.2025.0161189

@article{LAGHZAL2025,
title = {Mapping Artificial Intelligence Research in Automotive Manufacturing: A Bibliometric Study},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0161189},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0161189},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {11},
author = {Sara OULED LAGHZAL and EL OUADI Abdelmajid}
}