The Popularity of AI-Generated Music: Trends, Genres, and Influencing Factors

Music is an integral part of life, and in recent years, machine learning has been increasingly applied to music generation. While many existing review papers focus on the models used and the overall development of the field, few have examined the popularity of different musical genres within AI-generated music. This paper aims to fill that gap by analyzing the popularity of AI-generated music from two angles: overall trends and genre-specific trends. It also offers possible explanations for the patterns observed. To assess popularity, the number of related publications indexed on Google Scholar each year is collected and analyzed. The paper is divided into two main sections. The first examines the general rise in interest in AI-generated music, particularly the sharp increase after 2016. This surge may be attributed to developments such as more efficient models, improved and affordable hardware, and broader access to training data. The second section focuses on the three most popular genres in AI music generation, comparing their relative popularity and exploring the reasons behind these trends. Factors such as data availability, genre complexity, and real-world popularity are discussed as possible explanations.