This study analyzes the artificial intelligence (AI) literacy levels of music education students and explores how future music educators perceive and integrate AI tools within creative and instructional contexts. The research group consisted of 143 students enrolled in music education programs from different faculties, such as Education, Fine Arts, and Conservatory. Participants were selected through a purposeful sampling technique, ensuring inclusion of individuals likely to encounter AI in educational and performance settings. The study employed a causal-comparative (ex post facto) design, which enables examination of naturally existing groups differing in characteristics such as prior exposure to or familiarity with AI technologies. Quantitative data were analyzed to compare students’ AI literacy levels across demographic variables, including gender, type of high school graduated from, academic achievement level, and prior knowledge of AI. However, it was determined that the artificial intelligence literacy level of music teacher candidates who have knowledge about artificial intelligence programmes and use artificial intelligence programmes in music education is significant. Results indicated that students’ AI literacy levels were at a medium level. No significant differences were found in AI literacy by gender, type of high school graduated from, academic achievement, or frequency of internet use. However, significant differences were observed among students from different faculties, as well as among those who had prior knowledge of AI programs, used AI applications in music and music education, and used them more frequently. These findings suggest that direct engagement with AI tools contributes to higher literacy levels.