AI IN THE MUSIC INDUSTRY : TRANSFORMING CREATIVE PROCESSES

Abstract

Purpose of the study. This article aims to examine the role of artificial intelligence (AI) in transforming creative processes within the modern music industry and to analyze the cultural implications of human3machine co-creativity.
The study investigates how AI technologies redefine traditional notions of musical authorship, aesthetics, and emotional expressivity, offering new models of collaboration between human artists and algorithmic systems.
Research methods. The research is based on an interdisciplinary methodological framework that integrates cultural analysis, aesthetic criticism, and comparative techniques. The study also employs a critical review of relevant academic literature and explores contemporary examples of AI-assisted music production, including models such as Music Transformer, WaveNet Autoencoder, and generative platforms like AIVA and Flow Machines. The study further draws on empirical cases from the AI Song Contest and other hybrid collaborative practices.
Results. The findings reveal that artificial intelligence has become more than a tool; it acts as an autonomous agent capable of generating structurally complex, harmonically rich, and stylistically nuanced compositions. AI9s ability to process massive musical datasets and generate outputs based on learned stylistic models enables unprecedented creative experimentation.
However, the increasing algorithmization of musical creativity also raises a set of cultural and ethical concerns-particularly regarding authorship, authenticity, and the preservation of artistic individuality in the face of machine-led standardization.
Existing scholarship remains fragmented, often lacking a comprehensive cultural perspective on the implications of AI in music.
Scientific novelty. This article contributes to the growing body of cultural research on AI by proposing a critical rethinking of creativity as a hybrid, co-constructed process. It is one of the first Ukrainian academic contributions to frame AI not merely as a technological innovation but as a cultural actor that reshapes the value systems and production logic of contemporary musical art. The paper outlines prospective pathways for harmonizing traditional and algorithmic methods of music creation within the broader context of digital culture.