The music industry's royalty system is a complex machine that, against all odds, works remarkably well at scale. It was designed for a world defined by scarcity, and artificial intelligence now threatens that assumption by making content effectively limitless. Faced with calls for a full economic reset, a more credible argument is taking shape: before rewriting the rules, the industry needs a serious period of measurement to understand what this new reality actually changes.
The argument comes from Thomas Sachson, a veteran executive whose 25-year career spans technology, entertainment, and finance. Now a Transmedia Challenge Manager at Sony Pictures Entertainment, he has held leadership roles at Sony Music and Intel, where he focused on immersive media and machine learning initiatives. A licensed attorney with 13 issued patents, Sachson brings together creative rights, technical innovation, and economic pragmatism. In his view, a moment of this magnitude calls for slowing structural change while accelerating the collection of credible data.
"It’s too early to definitively say what the royalty models should look like when it comes to AI. We need to create a system for collecting honest data before making big structural changes," says Sachson. His strategy splits the problem in two: taking firm, immediate action on the ethics of AI training while advocating for patience on royalty reform.
- The three C's: In the midst of ongoing legal and policy debates around copyright, he points to a small set of baseline requirements that should apply regardless of how future payout models evolve. "If an AI is training on somebody else's intellectual property, they need to be compensated, they need consent, and credit needs to be given to the artist," says Sachson. "The three C's: credit, compensation, and consent. That's table stakes for AI and music."
His caution on economics directly informs his proposal for how to study it: creating new data "primitives" to capture a listener's true economic intent before redesigning any models. In his own paper, he outlines a hybrid system where fans could use a "dial" to allocate their subscription money between the standard pooled model and a user-centric model, a concept being explored by platforms like Deezer and SoundCloud with its fan-powered royalties.
- Dollars for data: For Sachson, however, the model's primary innovation is the novel layer of data it could produce. "Every time I push a penny towards one bucket or another, that data accrues and starts informing the labels and the artists not just what I'm listening to, but how I value it. That's a very different distinction," he notes. "It's a subtle one, but powerful."
Sachson’s model also acknowledges a practical risk: most listeners don’t want to micromanage their royalties every month. His answer is a personal AI agent that learns a listener’s values and quietly handles allocation on their behalf, within guardrails set by new and legally-compliant licensing agreements.
- Mozart in the machine: He places AI in a longer historical arc, not as an industry-breaking force but as the latest powerful tool to reshape creative work. From that perspective, he’s notably optimistic, seeing AI less as a threat and more as a way to widen access to creation and reduce the odds that great talent goes unheard. "AI could usher in a golden age of creativity, ensuring there's not going to be that Mozart who goes undiscovered. They can create and they can publish. And if what they're producing is substantial and it's good, I think people will notice and it will surface to the top."
He views AI's permanence as a creative tool that challenges existing streaming models. And because AI is here to stay, he believes it's all the more important not to rush into a new payout structure without understanding the consequences. He champions moving quickly to collect and assess new forms of data, but believes that speed should not extend to overhauling royalty structures.
Ultimately, Sachson frames the path forward as a case for restraint paired with rigor. "We as an industry really need to not make rash decisions or judgments before we've collected a lot of data on what the artist community wants, what the listener community wants, and how the distribution and management layer—the DSPs, labels, and rights owners—can facilitate a fair and equitable ecosystem," he concludes.