Author: Brandon Yu
Graphics: Sylvia Tirado
The BRB Bottomline: AI is rapidly transforming the music industry, from production to distribution, raising questions about the originality of creative work.
Introduction
Over the past few years, Artificial Intelligence has ventured into a number of different industries, and music has become one of its newest focuses. Recently developed AI tools have begun to transform a number of processes involved in professional and recreational music from ideation and creation, to market analysis and trend prediction.
The Growth of AI in Music
The appeal of AI tools in the music space is obvious: opportunity to transform ideas to a tangible product. AI use in all sectors of art, not exclusively music, has allowed users to explore unique thinking, contrast norms, and foster novel ideas. With new, creatively-oriented AI tools in hand, people, from beginners to experts, can suddenly produce fully-fledged artistic pieces based solely on ideas and visions. It is this vast increase in accessibility that has fueled music AI’s recent spread. What exactly does this growth look like? The global Artificial Intelligence in music and audio market size was estimated to be valued at $5.40 billion in 2022. This valuation is projected to increase to $22.89 billion by 2030. The growth of AI music in industry can be explained by recent corporate initiatives, especially the uprising of music AI startups and their acquisitions. 2022 was a huge year for the entry of AI into the music industry via large corporations acquiring novel AI tools. Apple’s acquisition of AI Music, a British startup aiming to use AI to shift music between genres, was suspected as a move toward assisting Apple’s music and video editing softwares. The Korean music label, HYBE, acquired Supertone, a company specializing in synthetic voice technology. Supertone’s novel technology is planned to prove useful in allowing artists to avoid large gaps in content production. The significant shifts in the market act as indicators that AI is soon to become a commonality in music.
Music Composition and Production
The domain most significantly impacted by AI in recent years is music composition. AI has entirely altered the process of music composition through tools that are able to generate melodies, harmonies, and even entire tracks. One notable AI engine doing exactly this is Google’s Magenta, an open-source project that utilizes machine learning to create audio and visual art. Other growing tools include Amper Music, which emphasizes quick and efficiently generated tracks, and AIVA, specializing in creating emotional soundtracks for purposes such as video game scoring. Tools like these have not only allowed casual creators to break into the music composition space, but have swiftly made their way into being used on a professional level. Surveys have revealed that roughly 25% of music producers currently use AI during some portion of their workflow, whether it be stem splitting, mastering, or even generating full tracks. A majority of producers not using AI, around 82%, make this decision to preserve their personal creativity. The remaining portion simply choose not to due to low quality of AI and concerns over copyright. Although only a small portion of professionals have implemented AI into their work, it is only time before improving technology and clarified regulation make AI more standard in the music production industry.
Music Distribution and Personalization
In addition to altering the way people produce music, AI tools have changed the way people consume music. Large streaming platforms, such as Spotify, have begun using AI to curate personalized playlists and music recommendations. These algorithms draw from users’ listening habits, style and genre preferences, and even the sound properties of songs. AI is not limited to just impacting the listener experience. Algorithms that assess trends and marketability have changed how music is being distributed. Universal Music Group, as an example, has begun using AI to predict the “trendiness” of new releases, achieving an 87% accuracy rate. This allows for marketing and promotion efforts to be concentrated more toward songs with greater potential.
Challenges and Controversies
Despite AI’s promising future in streamlining music processes, it has opened up challenges with regard to rules and regulations. One of the most significant concerns regards copyright infringement and theft of music styles. AI has blurred the definitions of “original music,” opening up difficulty in deciding who or what should own rights to certain music. In 2023, Universal Music Group, along with other large record labels, filed lawsuits against two AI music engines, Suno and Udio. The platforms had used existing music to train their AI algorithms, resulting in generated music resembling the qualities of known artists such as Michael Jackson and ABBA. UMG and company felt this violated the ownership of these artists, while Suno and Udio found it fair under copyright law. Despite developments, no conclusions have been made, and the case remains ongoing. This is just one example of the complications that have happened and will ensue as AI continues growing in the music space. Some believe that there should be a strict line drawn between AI-generated and manmade music, with around 90% of listeners feeling that AI-generated music should be properly labeled and distinguished. Others feel that transparency is not necessary. Calls for government intervention in these challenges have been made, such as the No Fakes Act intending to protect artists’ voices. However, no regulations have been fully enacted. These controversies demonstrate the complexity and balance involved in music AI.
What’s Next?
As AI continues reshaping music, both professionally and casually, creators, consumers, and stakeholders must find the balance between enabling creativity and protecting rights. As legal battles resolve, precedents will be set regarding the rights and wrongs of using AI in the music space. With all these unknowns, it is only safe to say that AI will continue to grow in capability and reach.
Take-Home Points
- The growth of AI in the music industry can be seen in market behavior; the global Artificial Intelligence in music and audio market size was estimated to be valued at $5.40 billion in 2022 and projected to increase to $22.89 billion by 2030.
- 25% of music producers use AI software in their workflow, and this percentage is expected to grow with the improvement of AI tools.
- AI has become powerful if predicting trends in the music market, allowing for artists to hone in on certain styles of music and focus promotion and marketing.
- Controversies have developed regarding music copyright and transparency regarding the use of AI in marketed music.
- Passing regulation regarding the use of AI in music via government entities have been attempted but not found success.