Artificial intelligence (AI) has been transforming the music industry for decades. Within the realm of music education, current research on the implementation of AI applications falls into eight main categories: virtual reality and augmented reality; learning personalization; intelligent tutoring systems; composition assistants; improved historical and contextual learning; assessment systems; interactive ear training and music theory systems; and tools for music collaboration and performance. Even with all the advancements in AI-driven technology and platforms, however, piano pedagogy in higher education has largely remained unchanged, retaining its core traditional teaching model of weekly, one-on-one, face-to-face instruction on acoustic instruments. In this age of rapid global AI revolution, the relevance of AI technology to, and its implementation in, the piano lesson model at the university level bears consideration.Using a quantitative cross-sectional survey design, we investigate the current landscape of AI technology adoption and the prevailing attitudes toward its use within the domain of piano education, sampling piano faculty and students in normal universities (teachers’ training institutions) and liberal arts universities in both the United States and China. The survey provides a barometer of needs, perceptions, experiences, and attitudes towards the integration of AI and technology into piano pedagogy at the higher education level, while also collecting important background data on parameters such as curriculum design and student satisfaction. Findings will identify both common and unique challenges that educators and students currently face with and without AI technology, inform the design of human-in-the-loop platforms to better address the needs of target demographics and mine the tacit knowledge embedded in teacher-to-student transmission, and offer administrators evidence-based roadmaps for further faculty development and integration of ethical, effective AI in applied music education.