The music industry has reached a turning point. Hallwood Media Group’s signing of imoliver, the most-streamed creator on AI platform Suno, was not just another record deal. It marked the arrival of the “music designer.” As generative tools shift from novelty to mainstream, the very definitions of artistry, ownership, and value are being rewritten in real time, leaving the industry in a lawless “wild west.”
We spoke with Joey Nix, Co-Founder and CMO of The Jays Group, a boutique consultancy that helps companies in creative technology scale growth and revenue. A veteran marketing executive, Nix’s career has placed her at the epicenter of music, technology, and culture. Her experience driving explosive growth at music software company Output, which launched its own AI-assistive tools, and her work as a consultant for industry giants like Kobalt Music and Beatport, give her a uniquely informed perspective on the collision of human creativity and artificial intelligence. For Nix, the signing of a "music designer" crystallized the industry's single most pressing crisis.
- Co-writer or tool?: "Where is the line, and what is the percentage split? We understand these splits when it comes to co-writers," Nix explained. "But what about AI systems, or even non-AI technology? How much ownership does something like Ableton take? Are we treating GenAI as a co-writer, or as a tool like a DAW or a guitar? Right now it’s the wild west, with no clear way to define what is too much and what deserves credit."
The ambiguity has thrown the industry into a state of legal and financial vertigo. The "co-writer vs. tool" debate isn't academic; it's a direct challenge to the entire economic model of music. Nix laid out the unprecedented complexity of the new value chain, where a single track could have multiple, competing claimants.
- The copyright quagmire: "Does the copyright belong to that designer or curator or prompt engineer? Does the copyright get split with the AI company and algorithms that created it? And then does that copyright then get split with the artists whose music the model was trained on?" she asked. "The ethical dilemma that we're facing right now is how much attribution and therefore copyright ownership and therefore royalties and actual money goes back to the artists on which these LLMs are trained."
As the industry grapples with these foundational questions, business strategy will inevitably follow the money. Nix explained that the rise of "music designers" may force a shift in how talent is discovered, but the extent of that shift depends entirely on commercial success. However, she warned that the most significant impact may not be felt at the top of the charts, but in the fragile ecosystem of emerging artists.
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The long tail of artistry: "The long tail of artistry will change the most, where a musician today might be a singer-songwriter with just a guitar and a few samples or drum tracks," Nix explained. "Maybe they're making a couple hundred dollars a month off of their Spotify streams. Those are the artists who one day could be the next Chappell Roan. They might get ousted because they're in their infancy of their career, battling against Gen AI that isn't limited by time and expense and output."
I still think that there will be a distinction between AI music compared to the songs that win a Grammy or get sung at a karaoke bar 30 years from now. There might be billions of GenAI songs out there, but there's only so many Don't Stop Believin's that'll come out of it. This enduring connection comes from a place AI can't access: human pain and storytelling.Joey Nix - Co-Founder and CMO | The Jays GroupDespite the threat to aspiring musicians, Nix argued for the irreplaceable power of human expression. She argued that while AI can generate endless content, it cannot replicate the emotional depth that creates timeless art. To illustrate the difference, she proposed a simple, powerful metric for cultural endurance.
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The karaoke bar test: "I still think that there will be a distinction between AI music compared to the songs that win a Grammy or get sung at a karaoke bar 30 years from now," she explained. "There might be billions of GenAI songs out there, but there's only so many Don't Stop Believin's that'll come out of it." This enduring connection comes from a place AI can't access: "human pain and storytelling." The image of a busker "wailing their heart out" in a New York subway, she said, is something technology cannot simulate.
Given the importance of the human element, many have called for transparency, demanding that AI-generated music be clearly labeled. Nix, however, was deeply skeptical that such a system will ever be implemented effectively, pointing to a long history of socially accepted manipulation and unenforced regulations.
- The transparency fallacy: "I just don't see it playing out at all," she said. "When we think about a magazine cover, we know that the hair is photoshopped, we know the skin has been retouched, but we've never had to provide disclosure for changing someone's likeness." She compared it to FTC guidelines for sponsored content, which are routinely ignored. "If we can't even follow brand ad FTC guidelines properly, how is anyone going to follow an AI generated guideline?"
"I am excited about AI democratizing access. I think we are all born with musicality; a baby sings before it speaks. I love the idea that this is a form of creativity that everyone will be able to access," she said. "But I am wary of the state of being able to earn a living as a musician. If we don't figure out copyright royalties and the sheer volume of this democratization, how is anyone ever going to make a living from being a musician again? If people can't make a living out of being a musician, are we going to get good music? Because people should be compensated for their art."