Independent Music Publishers Draw a Hard Line on Generative AI Valuation with Equal Pay Demand

The global independent music publishing sector has officially drawn a line in the sand regarding the commercialization of artificial intelligence, issuing a comprehensive licensing framework that seeks to fundamentally alter how digital royalties are distributed. Published jointly by the Independent Music Publishers International Forum (IMPF) and digital licensing hub IMPEL, the new guidelines establish a non-negotiable principle for the artificial intelligence era: the underlying song must be valued equally to the sound recording.

This aggressive stance targets a historic structural imbalance that has plagued the music industry for decades. In traditional music streaming ecosystems, master rights—representing the specific sound recording owned typically by record labels—command a significantly larger share of streaming revenue than composition rights, which belong to the songwriters and publishers. By releasing this framework, independent publishers are signaling that they will not allow technology companies and major music conglomerates to replicate these outdated valuation models within the rapidly expanding generative AI market.

The Core Principle: Parity Between Composition and Master

At the heart of the newly proposed framework is the assertion that generative artificial intelligence fundamentally relies on songwriting, lyrics, melodies, and compositions for training, prompting, generation, output, and commercialization. Consequently, the groups argue that any licensing model that treats the song as a minor component of value while allocating the vast majority of revenues to master rights is entirely unacceptable.

According to IMPF and IMPEL, licence payments for the two distinct copyrights contained within every musical track—the master recording right and the underlying composition right—must be more or less equal, barring any exceptional salient factors. This demand challenges the operational precedent set by digital streaming platforms over the past two decades, where record labels routinely secured the lion’s share of incoming revenues.

The friction between recording rights and publishing rights is not new, but the advent of generative AI has amplified the urgency of the debate. Major music conglomerates, which operate both record labels and publishing arms, have historically faced accusations of favoring master-side revenues. Because publishing deals typically require a much higher percentage of royalties to be passed directly to the songwriter—whereas traditional record deals often leave artists with a minority share of master revenues—critics have long alleged a conflict of interest. While major publishers consistently deny that these internal dynamics influence market negotiations, the independent sector remains profoundly skeptical. With AI deals now being negotiated and signed at a relentless pace, indie publishers argue that failing to secure parity now will institutionalize systemic disadvantages for generations of songwriters.

Navigating Complex Income Streams and Legal Settlements

The economic architecture of generative AI licensing is vastly more complex than traditional streaming models. The IMPF and IMPEL framework highlights several distinct operational hurdles that technology platforms and rightsholders must navigate as commercial agreements take shape.

First, music-driven AI systems often generate multiple distinct income streams. There is typically a baseline licensing fee associated with training the underlying foundational AI model on vast corpora of copyrighted audio data. Additionally, there are downstream commercial streams generated when users prompt the AI to produce specific outputs, utilize remix or mashup tools incorporating existing tracks, or exploit the distinct vocal characteristics of human performers. Major record labels have been aggressively pressuring tech partners to prioritize output tools that utilize existing catalog tracks, complicating the distribution pipeline and necessitating separate accounting mechanisms for training versus output exploitation.

Second, the methodology for allocating training revenue across vast catalogs remains a contentious issue. Rightsholders face critical questions regarding whether training income should be distributed evenly across entire catalogs or allocated via complex data-tracking systems that attempt to quantify the exact influence of individual works on an AI model’s training subset. Furthermore, many initial commercial AI deals currently being struck incorporate legal settlements. These settlements compensate rightsholders for historical copyright infringement, given that numerous technology companies ingested massive quantities of music without permission during the initial development phases of their models. Determining how to fairly distribute these retroactive settlement funds alongside forward-looking operational royalties adds another layer of administrative complexity.

The Demand for Radical Transparency

Recognizing these administrative and legal minefields, the IMPF and IMPEL framework places a heavy emphasis on transparency as a mandatory prerequisite for any technological partnership. The guidelines explicitly state that rightsholders must have complete clarity regarding what material is being licensed, the specific nature of how works are utilized within algorithmic architectures, the mechanisms governing attribution, and the exact formulas used to calculate revenues and apply deductions.

The framework demands clear legal and financial delineation between payments designated for past use, model training, direct outputs, and future commercial exploitation. Furthermore, any administrative deductions, operational costs, or revenue calculations imposed by intermediaries must be fully justified, transparent, and applied equitably across the board.

Industry Response and Strategic Implications

The release of the framework has garnered widespread support across the independent creative community. IMPF President Annette Barrett emphasized the vital importance of collective advocacy during a period of unprecedented technological disruption.

"IMPF exists to give independent publishers and the songwriters we represent a collective voice, a mission that has never mattered more, as our industry navigates disruptive change and new rules are being written," Barrett stated. "The song needs protecting as the keystone of it all."

The broader implications of this framework extend far beyond independent publishing circles. As artificial intelligence companies face increasing legal pressure from copyright holders—culminating in major lawsuits filed by both independent and major music entities—technology firms are increasingly eager to transition from an era of unauthorized data scraping to one of formal licensing agreements.

By uniting under a clear, non-negotiable set of valuation and transparency principles, independent publishers are attempting to preemptively shape the commercial standards of the generative AI sector. Whether major technology corporations and hybrid major music companies will concede to composition-master parity remains to be seen. However, by establishing these benchmarks early, the independent sector has ensured that the economic value of the songwriter will remain a central point of contention in the ongoing legal and commercial evolution of artificial intelligence.