Musical AI tracks creators and pays them for using their content

The world of music is rapidly evolving, and with the rise of artificial intelligence-generated content, a fundamental question has emerged: how do we ensure that the creators whose work fuels these systems are credited and compensated?

To tackle this challenge, two major forces in the Canadian music ecosystem are joining forces. SOCAN (Society of Composers, Authors and Music Publishers), Canada’s largest member-owned music rights organization, is partnering with Musical AI, a cutting-edge Canadian rights technology company.

This collaboration is designed to lay the groundwork for a fairer future by establishing clear principles: creators should have the power to decide whether their music is used by AI systems, and they deserve proper attribution and payment whenever their work contributes to an AI-generated output.

The partnership isn’t about immediately implementing a new royalty system; instead, it focuses on developing the essential technology, guidelines, and rights-management framework necessary to make such a system possible. It is a strategic move aimed at addressing the complex reality of music in the age of AI.

At the heart of the initiative is the principle of consent. The organizations are exploring Musical AI’s tools to provide songwriters, composers, and publishers with scalable methods to authorize or decline specific uses of their catalogs by AI systems. This provides a much-needed structure for managing permissions across vast musical catalogs.

Sean Power, CEO of Musical AI, emphasized the crucial sequence of action: “The first step is consent, the next step is attribution that can show how music contributes to an output and how value should flow to artists and songwriters.”

This focus on transparency is vital. In the current AI landscape, rights holders often struggle to determine whether their compositions were used to train systems or influence commercial outcomes. This partnership aims to resolve that ambiguity by creating a traceable record of musical influence.

Musical AI’s attribution technology analyzes AI-generated outputs to pinpoint the licensed source material that influenced them. By assessing contributions from both sound recordings and underlying musical compositions, the system generates reports that can support licensing, accountability, and fair compensation—essentially creating a digital split sheet for AI music.

This infrastructure is especially transformative for rights organizations like SOCAN. SOCAN already manages license fees and distributes royalties; however, when an AI output incorporates multiple existing works, having a reliable way to identify these contributions becomes critical for matching licenses and distributing money correctly.

By developing this attribution framework, the partnership aims to ensure that music creators are paid fairly when their work is used by artificial intelligence. This effort aligns with a broader Canadian goal: positioning AI adoption as a source of responsible innovation that respects and recognizes the profound value of human creativity and cultural identity.