The integration of artificial intelligence (AI) into engineering education is essential for fostering innovation, strategic thinking and interdisciplinary skills in the intelligent era. On this basis, this study aims to track and visually represent the research outputs associated with AI applications in engineering education, providing insights into the current research landscape and identifying areas for further investigation. The analysis offers theoretical and methodological direction for leveraging AI in engineering education. Utilising bibliometric methods, we conducted a comprehensive visualisation analysis of 378 core publications from the Web of Science (WoS) database, spanning from the beginning of the twenty-first century to the present. Our findings show a consistent rise in publication volume from 2000 to 2017, with a significant surge from 2018 to 2023. The study identifies the "International Journal of Engineering Education" and "Computer Applications in Engineering Education" as pivotal journals in the field. The research clusters around two central themes: essential supportive technologies and specific educational applications. Within engineering education, expert systems, data mining, prediction and machine learning are highlighted as key research areas. The field has evolved through distinct phases, starting with an early focus on technology support systems, moving to an emphasis on pedagogical applications, and currently striving for a balance between diverse technologies and practical applications.