Artificial intelligence (AI) is a game-changing technology that is increasingly being employed in higher education, particularly to enhance entrepreneurship, teaching, and learning. AI facilitates the creation of ideas, business planning, market analysis, problem-solving, and decision-making processes—all crucial components of entrepreneurship education. However, the effectiveness of AI integration is largely dependent on students' familiarity with the technology and their willingness to employ it in instructional activities. Therefore, the goal of this study was to investigate how Politeknik Merlimau Mechanical Engineering Department students enrolled in entrepreneurship courses relate to AI understanding and readiness for AI adoption. A quantitative survey study design involved 44 students from the Mechanical Engineering Department. Data was gathered using a standardized questionnaire that included information on demographics, AI knowledge, and preparedness for AI adoption. The reliability research demonstrated exceptional internal consistency, with Cronbach's alpha values of 0.939 for the AI knowing construct and 0.977 for the readiness construct. Descriptive analysis revealed that the respondents were well-versed in AI (M = 4.29, SD = 0.58) and ready to embrace it (M = 4.20, SD = 0.76). Pearson correlation analysis revealed a strong positive and statistically significant relationship between AI knowledge and readiness for AI adoption (r = 0.883, p < 0.001). The findings suggest that students who have a greater understanding of AI technology are more prepared and motivated to integrate AI into entrepreneurship education activities. This study highlights the importance of improving AI literacy, awareness, and competency development among Mechanical Engineering students in order to increase effective AI adoption in entrepreneurial education. In addition to helping Technical and Vocational Education and Training (TVET) institutions implement Education 4.0 programs, the findings provide educators, curriculum designers, and legislators with valuable information for developing AI-driven learning strategies.
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