This study conducts a bibliometric analysis of recent trends and emerging topics in the application of Artificial Intelligence (AI) in vocational education. AI technology holds significant potential to enhance accessibility, inclusivity, and equity in quality education. The research utilizes the Preferred Reporting Items for Systematic Reviews and Meta-Analyses approach to analyze publications from articles and conference papers published in the Scopus database between 2014 and 2023. The key findings indicate that AI is reshaping vocational education by personalizing learning experiences, improving curriculum development, and enhancing practical training through automation and robotics, particularly in the manufacturing and logistics sectors. Ethical issues, such as privacy and algorithmic bias, are also highlighted as key concerns. The bibliometric analysis reveals that journal articles have a higher citation count than conference papers, reflecting their greater influence in the field. Network visualization demonstrates the interconnection between AI, vocational education, and related concepts, such as e-learning and machine learning. Furthermore, AI contributes to the achievement of the United Nations Sustainable Development Goals (SDGs) 2030, particularly SDG 4 (quality education access), SDG 8 (decent work and economic growth), and SDG 9 (industry, innovation, and infrastructure). The study also identifies challenges that need to be addressed, including data privacy, infrastructure readiness, and teacher training, while providing guidance for future research and educational policy development. © 2025 The Authors
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