This article is written and presented by MatchTune.
Think about your favorite song. What makes it resonate so deeply? For many, it’s the artist’s raw emotion—the vulnerable experience behind its creation. This human connection is what makes music truly special — something AI can imitate but never replicate.
As generative AI continues to populate the music market, it threatens further dilution of compensation for human creators and rights holders—including independent creators already struggling under current licensing models. Such threats require proactive, timely solutions.
This article explores new ways to fairly compensate artists in the evolving landscape of generative AI, delving into the compensation gap and evaluating creative, emerging solutions that place IP back in the hands of humans.
Gen AI & Traditional Licensing: The Compensation Gap
For decades, licensing has been the backbone of music monetization. But for many, the system has long been stretched thin. With streaming royalties already so diluted that many musicians struggle to make a sustainable income, the rise of generative AI presents a new threat: models trained on vast libraries of commercial music without consent or compensation, saturating the market and diverting revenue from human creators.
It’s becoming clear: traditional licensing frameworks weren’t built to handle AI’s scale and complexity. As generative tools sample and learn from countless works, tracing usage and compensating original creators grows increasingly difficult. And even if licensing structures adapt, the royalties reaching rights holders risk becoming so fractional that they offer little meaningful protection—especially for independent artists already operating at the margins.
In the Gen AI era, there’s no one-size-fits-all solution to compensation—but several emerging models offer promising paths forward for music rights holders:
Reforming Licensing Structures
While traditional licensing remains foundational, it wasn’t built for the speed or scale of AI. Even with increased transparency in the training phase, royalty payouts may become so fractional that creators—especially independents—see little to no benefit. Adaptive licensing must evolve in tandem with broader industry reforms.
Exploring the Private Copy Model
This model proposes that AI developers pay a fixed levy for training on copyrighted content, regardless of how often individual works are used. Already used in some European media sectors, the private copy model could simplify rights management and ensure compensation without needing granular tracking.
Reinvesting Through Cultural Funds
If direct compensation proves too complex or diluted, AI companies could support music education, artist development, or funding initiatives. While not a replacement for royalties, these reinvestments could meaningfully support the ecosystem that generative models depend on.
As our industry navigates this new and threatening frontier, one core question remains:
“How can we protect the value of human creativity in an increasingly automated landscape?”
On July 10, MatchTune and A2IM will host a live webinar, “Threat to Opportunity: A Blueprint for Effective Rights Holder Compensation in an AI World.”
This collaborative session will explore the evolving compensation landscape, spotlight emerging solutions, and open the floor to industry voices across the independent music sector.
Whether you're an artist, label exec, publisher, or music industry professional, this is your opportunity to weigh in on one of the most urgent challenges facing our industry. We look forward to seeing you there!