The rapid evolution of AI-assisted audio tools ranging from machine-learning noise reduction and stem separation to procedural sound generation and spatialisation has begun to reshape the creative workflow for emerging sound practitioners. While these tools offer unprecedented speed, accessibility, and creative possibilities, their integration into sound design education remains inconsistent across institutions.
This paper explores how AI can be effectively embedded into higher-education creative audio curricula, drawing from practical case studies and workflow observations in film and game sound. I examine how tools such as voice-isolated dialogue repair, AI-assisted Foley synthesis, generative ambiences, and automated mixing systems can enhance foundational learning rather than replace human creativity.
The study also considers challenges: ethical authorship, over-reliance on automation, access inequality, and the risk of diminishing critical listening skills. Through a practitioner-focused lens, the paper proposes a balanced framework where AI functions as an augmentation of the student’s craft helping learners refine decision-making, expand sonic imagination, and accelerate iterative exploration.
By situating AI as a collaborative partner rather than a shortcut, the paper argues for a future-ready pedagogy that empowers both educators and students in creative audio disciplines.
