Mapping Organizational Readiness for Artificial Intelligence (AI) in Automotive After-Sales Services: A Bibliometric Study

This study presents a bibliometric analysis that maps the research landscape of organizational readiness for artificial intelligence (AI) within the automotive sector, with a particular focus on after-sales services. Utilizing the Scopus database, 370 peer-reviewed articles published between 2014 and 2024 were systematically analyzed using Biblioshiny to investigate publication trends, thematic evolution, keyword co-occurrence, and citation patterns. The analysis reveals a consistent growth in annual scientific production, indicating rising academic interest. However, keyword clustering and co-occurrence networks demonstrate that research is predominantly concentrated on technical implementations of AI, such as machine learning, automation, and Industry 4.0, while organizational readiness dimensions, including leadership, digital culture, and workforce capabilities, remain underrepresented. Citation trends further reflect this imbalance, as highly cited papers tend to emphasize technological advancements rather than organizational preparedness. Notably, after-sales service functions a key touchpoint for customer satisfaction and long-term value are largely absent from mainstream AI readiness discourse. These findings highlight a significant research gap in the context of AI adoption within service-oriented organizations. By identifying neglected areas and synthesizing emerging themes, this study provides theoretical insights and practical directions for future research into AI readiness within after-sales operations of the automotive industry.