AI Music Is Exposing a Hidden Infrastructure Gap in the Creator Economy

Seven million songs a day. That is how much music a single AI platform, Suno, now produces, according to an investor pitch deck obtained by Billboard. Enough to fill Spotify’s entire catalog every two weeks.

Suno raised $250 million in November 2025 at a $2.45 billion valuation. A year earlier, the three major labels had filed over $500 million in copyright claims against Suno and a rival platform, Udio. And by the end of 2025, each one of those labels had settled and signed licensing agreements instead.

That turnaround happened fast, and it settled the legal question. AI-assisted creation is part of the music industry now.

But the harder question is still very much open. Can the systems built to track and monetize creative work actually handle what AI-driven creation produces?

Right now, the answer is no, and that infrastructure gap extends well beyond music.

AI Breaks the Assumptions the Creator Economy Was Built On

The creator economy reached roughly $250 billion in 2024. Goldman Sachs projects $480 billion by 2027, and more aggressive estimates put it above $1 trillion by the early 2030s. But the infrastructure underneath all that growth was designed for a different era.

Legacy monetization systems assume scarcity of output, slow release cycles, and centralized rights ownership.

AI undercuts all three at once, and the scale of the mismatch is staggering. A single platform now generates 7 million songs a day at roughly a penny per song. The attribution and payment systems underneath were built to handle 100,000 new releases per year at best.

Goldman-Sachs also reports that the numbers on the creator side confirm this. Only 4% of creators globally earn over $100,000 a year. More than half earn under $15,000. And 58% report ongoing difficulties with monetization.

So, the infrastructure was already failing creators before AI entered the picture. Now that AI has removed the constraints those systems were built around, the gap between what gets created and what gets compensated will only grow larger.

Licensing Deals Manage Risk, But They Don’t Redesign the System

The major-label agreements with Suno and Udio were rational defensive moves. They resolved half a billion dollars in copyright litigation, established opt-in frameworks for artists, and created new revenue streams from licensed AI models. For the labels, these deals made sense as near-term risk management.

But look at what actually changed on the ground.

After its deal with Warner, Suno quietly changed its ownership terms. Language that previously told subscribers “you own the songs” disappeared. The updated policy now states that users are “generally not considered the owner” of their outputs, even on paid commercial plans.

Udio went further. Its revamped platform will prohibit users from downloading or sharing songs outside a closed environment. The model protects rights holders, but it also walls off the creative flow that drives music culture forward.

What these deals resolved was the legal question, but they left everything else untouched.

There is still no scalable way to attribute contributions across AI-assisted workflows, no mechanism for granular revenue participation, and no infrastructure for real-time monetization across platforms.

For investors who may be looking in this space, the distinction is very important.

Licensing agreements protect against downside risk. They do not create upside. And in a market where creation now happens at machine speed, the upside belongs to whoever builds the systems that can keep up.

Value Leaks When Infrastructure Doesn’t Scale

Every licensing deal signed in late 2025 runs on the same assumption that ownership can be defined at the point of creation and tracked through existing systems. In an AI-assisted environment, both of those assumptions are very wrong.

Think about what a typical workflow actually looks like now. A creator uses one AI model to generate a melody, a second to arrange it, and then records original vocals on top.

Who owns what percentage of that track? The AI providers have terms of service. The creator has a commercial license. The labels have opt-in agreements. But no system connects those layers into a single, auditable chain of attribution.

Now multiply that by 7 million songs a day.

The US Copyright Office ruled in early 2025 that purely AI-generated works cannot be copyrighted, while works with “sufficient human creative direction” can.

In practice, that creates a massive gray zone for exactly the kind of hybrid content these platforms are designed to produce.

The value leakage does not come from piracy or bad actors. It comes from the sheer operational complexity that existing systems were never built to handle. Revenue cannot flow accurately when ownership itself is ambiguous at every step of the production chain.

Blockchain-based infrastructure is built for exactly this kind of problem. Royalty splits can execute automatically through smart contracts the moment a track is played or sold.

Ownership records can travel with creative works across platforms and remix chains through on-chain provenance. And tokenized rights structures allow for granular revenue participation without routing everything through centralized intermediaries.

Over 70% of new creator-focused startups launched in 2025 have integrated some form of Web3 infrastructure. Creator economy startups raised $767 million globally between 2023 and 2024, with AI-focused infrastructure attracting the largest share at over $300 million.

Music Is Just the Beginning

Music is where this infrastructure gap became undeniable, but the same dynamics are already visible everywhere.

Disney and Universal sued Midjourney in mid-2025 over AI-generated copyrighted characters. The New York Times sued Perplexity AI for scraping millions of articles without compensation.

The pattern is always the same. Production costs collapse, output overwhelms existing tracking systems, and value leaks through infrastructure that was never built for this speed.

AI hasn’t broken the creator economy – it’s stress-tested it, exposing the limitations of systems built for scarcity, slow release cycles, and centralized control. We can clearly see that the next phase will be defined by the platforms that can track, allocate, and monetize creative value at machine speed.

For investors and operators, this represents a structural inflection point: the companies that solve these systemic challenges will capture the disproportionate upside of a rapidly scaling, AI-driven creator economy.