In Mechanical Engineering Education (MEE), Artificial Intelligence (AI) is transforming research, teaching, and learning methodologies. Applications of AI, such as computer vision and Machine Learning (ML), facilitate automated tests, virtual labs, and personalized learning. This research aims to investigate the influence of AI tools on MEE. Accordingly, this study involved 78 undergraduate Mechanical Engineering (ME) students at Arak University, predominantly male (≈80%), with ages ranging from 19 to 39 years (mean = 22.7, standard deviation = 3.4). Most participants (78.2%) were between 20 and 23 years old, representing a typical demographic of undergraduates nearing program completion. These characteristics align with the study’s focus on undergraduate students as a key user group of AI tools in academic contexts. The results of this study are categorised into five main groups, namely familiarity and self-assessment, usage patterns, educational and course-specific usage, perceived impact as well as concerns and risks. The findings reveal that although the majority of students demonstrate moderate or higher proficiency, very high expertise is still limited. Moreover, the evidence highlights that acquiring core conceptual knowledge is the central motivation behind students’ use of AI tools. Furthermore, the data show that education was the leading motivation for AI use (47%), with ChatGPT serving as the most commonly employed tool (47%). This work provides a valuable resource for researchers, educators, and policymakers seeking effective AI integration strategies in MEE.
