The disruptor: How generative AI is challenging sync licensing in the music industry

In the rapidly evolving music industry, the traditional model of sync licensing is facing significant challenges posed by the advent of generative AI tools. These tools, such as Suno and Udio, have revolutionised the way music is created by allowing users to generate entire songs almost instantaneously and at no cost. This technological advancement threatens to disrupt the existing ecosystem where rights holders already struggle to earn between $0.003 and $0.005 per stream amidst the staggering competition of 120,000 songs uploaded daily to streaming platforms.

Sync licensing refers to the process of integrating music into visual media such as films, television shows, advertisements, or video games. This not only serves to enhance storytelling but also provides substantial revenue potential for artists through various rights, including mechanical, performance, sync, and master rights. Unlike streaming, where revenue is minimal, a single sync placement can bring significant financial returns, sometimes reaching several hundred thousand dollars. Additionally, it offers artists a platform for increased exposure; notable examples include Baby Queen, who gained a million new listeners after her track featured in Netflix’s series “Heartstopper”.

The potential for generative AI to upend this model is becoming increasingly apparent. With AI-produced music being both rapid and cost-effective, it poses a viable alternative for advertisers and content creators who traditionally rely on human composers and complex licensing agreements. This shift has caught the attention of major record labels, with Sony Music Entertainment, Universal Music Group’s UMG Records, and Warner Records reportedly taking legal action against Suno and Udio for allegedly using copyrighted material without permission to train their AI models.

In response to these challenges, new initiatives are emerging to mitigate the impact of AI on the music industry. Organisations such as Fairly Trained are certifying AI training data obtained with the consent of original creators. Ircam Amplify has introduced a tool that identifies AI-generated tracks, thereby assisting industry stakeholders in distinguishing between human and AI-created music.

Moreover, innovations like Bridge.audio’s descriptive AI tools aim to assist artists by improving discoverability rather than replacing them. Bridge.audio’s technology auto-tags tracks based on criteria like genre, mood, and lyrical content, enabling rapid and precise matching of music to projects. By October 2024, Bridge Sync, a commission-free sync marketplace by Bridge.audio, had secured participation from over 250 labels and nearly 100,000 tracks, indicating a growing acceptance of AI as a facilitator of human creativity.

The core challenge remains balancing the potential of AI-driven efficiencies with preserving the intrinsic value of human-made music. While generative AI provides an appealing proposition to industries looking to cut costs on music production, it risks diminishing the market for human creativity. Nevertheless, tools like those by Bridge.audio help ensure technology serves to enhance, rather than supplant, the human element in music. As the industry navigates these new technological landscapes, finding equilibrium remains crucial for future sustainability.

Source: Noah Wire Services