How music AI attribution actually works

The state of music AI today can be measured in the millions — millions of dollars raised, millions of users engaged, millions of AI-generated tracks uploaded to streaming services.

As the market continues to grow at breathtaking speed, an urgent business question has emerged: Who deserves credit and compensation when AI generates music? The answer could determine how billions in potential revenue flow through the music economy in the coming years.

Introducing attribution

Attribution — or the linking of AI outputs back to the specific training inputs that influenced them — underpins the ideal of a more granular rights holder compensation framework for AI.

Unlike copyright or deepfake detection systems that simply flag similarity or infringement, attribution aims to establish causal relationships between inputs and outputs. The concept overlaps with the fields of interpretability and explainability (XAI), which seek to understand how a model produces output for a given input.

For the music industry, attribution tech can help answer questions like:

• Which songs in the training data most influenced this output?
• How strong was each influence, and how should we quantify it?
• What specific musical elements were borrowed or transformed?

Several startups are tackling this complex problem with their own distinct approaches. Musical AI, Sureel, and Soundverse promise more granular, model-level tracking of influence, while others like LANDR, Source Audio, and Lemonaide offer simpler, pro-rata splits based on total dataset contributions. These ventures are also actively brokering a new generation of AI licensing deals between developers and rights holders, helping shape industry standards ahead of regulation.

In the sections ahead, we'll examine some of the technical underpinnings of attribution, the commercial frameworks being built around them, and the challenges in deploying these tools at scale. More than a mere technical curiosity, attribution will likely determine how — and for whom — the music industry thrives in an AI-centric future.

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