Navigating the Uncharted Waters of Generative AI in Music

Vicki Nauman, the founder and CEO of CrossBorderWorks, a music tech consulting and advisory firm, shares her insights on the evolving landscape of generative AI in the music industry. As a digital music veteran with extensive experience in the field, Nauman provides a comprehensive perspective on the challenges and opportunities presented by this disruptive technology.

Unlocking the Potential of Generative AI in Music

The Shifting Landscape of Generative AI

Generative AI is undergoing a significant transition, moving from a disruptive force to a sustainable part of the digital music economy. The road ahead may not be smooth, and the long-term impact of this technology remains uncertain. However, one thing is clear: like previous disruptions in the music industry, the path forward leads to licensing.

The Foundations of the Music Business

The music business is built on an intellectual property foundation, much like many technology and gaming companies. The key difference lies in the ease with which music can be integrated into third-party websites, apps, and experiences, and the ability of music to attract audiences and foster platform adoption. When this collision occurs, and someone else benefits from an artist's music, an exchange of value takes place, which is the lifeblood of how artists, labels, publishers, and collectives generate revenue.

The Complexities of Music Licensing

Music licensing has never been an easy task, despite the persistent arguments made by tech entrepreneurs who fail to understand the intricacies involved. From the earliest days of music disruption with illegal file-sharing, companies have claimed that copyright is outdated and that music should flow freely. However, the industry has adapted and figured out solutions for downloads, radio-style streaming, on-demand streaming, live streaming, digital fitness, TV/film, and games. Generative AI will also need to navigate this complex landscape.

The Licensing Dilemma: Permission or Forgiveness?

When it comes to music, companies often face a binary choice: seek permission (licensing) or ask for forgiveness. Licensing, while a mysterious process to many, involves four key elements: creating viable technology, assessing the necessary music rights, developing a business model that incorporates payment for music, and presenting this package to music rights holders. This process can be time-consuming, but it is the only sustainable path forward.Forgiveness, on the other hand, is a riskier approach. If a company is small and insignificant, it may be able to fly under the radar. However, once a successful product is built, the company becomes visible and exposed if it has not properly licensed the music. The consequences can be severe, often resulting in expensive legal battles and the potential loss of the company's potential.

Navigating the Generative AI Landscape

In the case of generative AI, many companies have initially built their models by training on unlicensed music and content, either seeking legal solutions, shuttering their operations, or believing that forgiveness is a viable option. However, the music industry is not known for its speed, and its complex rights structures make it challenging to model a legal approach. Ultimately, anyone who wants to work with music must address the issue of intellectual property rights.While major rights holders may not be ready to enable companies to train and generate new songs from their catalogs, smaller production libraries and catalogs are open to this opportunity. Generative AI companies must focus on their use case, user experience, and engagement, rather than simply adding more music to existing streaming platforms. The killer app for generative AI in music may lie in areas such as new social platforms, gaming, artist-fan collaborations, or industrial applications.

Building the Future of Generative AI in Music

As generative AI continues to evolve, new solutions are emerging that provide rights holders with greater control and visibility, such as rights management, generative AI detection, and attribution. These will become part of the legal ecosystem surrounding generative AI in music.For companies interested in innovating with generative AI in music, the path forward includes licensing existing music and engaging customers to monetize it as a baseline. Generative AI companies have a unique opportunity to step up and help build this new music economy, but they must be prepared to navigate the complex landscape of music licensing and intellectual property rights.