The Real Fight in Music Isn’t Over Who Makes the Song. It’s Over Who Counts It
A songwriter wakes up to find a 15-second snippet of her track soundtracking two million short-form videos overnight. Somewhere in the back offices of a label, a distributor, and three collection societies, that moment has already split into millions of individually payable events across dozens of territories, each with its own rules, splits, and currencies. Nobody in that chain can tell the songwriter what it’s worth, or even when they’ll know. Meanwhile, her phone is blowing up.
Here is the paradox at the center of the business. We have spent years debating who owns a machine-made song and whether synthetic tracks dilute the pool. Real questions, all of them. But they assume an industry that can already account for the music it has. It can’t. The most sophisticated argument about who deserves a royalty is worthless if the system underneath can’t calculate, route, and prove that payment. That gap, between the transparency the industry promises artists and the systems that can deliver it, won’t be settled by lawyers or lobbyists. It’ll be settled by engineering
Every music company is now a data company
A modern music company is not really in the business of songs anymore. It is in the business of data about songs: who played them, where, under which contract, owed to whom, in what currency. Rights, royalties, and consumption together form one of the most complex data problems in any industry, rivaling what we associate with global banking or telecoms.
Most companies still treat this as an administrative burden. The ones pulling ahead treat it as their core asset. Once you accept that the catalog is really a data estate, the question changes from “how do we account for the past” to “how do we turn this data into intelligence about the future.”
Attribution starts with the match
Every royalty begins as a usage report. Streaming services and short-form video platforms send rights holders enormous volumes of usage data, but a play only becomes money once it’s matched to the right recording, the right composition, and the right owners. That match depends on identifiers: ISRCs for recordings, ISWCs for compositions, and IPI numbers for writers and publishers. When those identifiers are missing, inconsistent, or wrong, the system can’t attribute the usage. It sits unmatched, and the money it represents can end up in pools of unclaimed royalties that are eventually distributed by market share instead of to the people who earned it.
Short-form video makes attribution harder. A clip might use a sped-up version, a remix, or a few seconds of a track buried under dialogue. Audio fingerprinting can identify the recording, but the recording is only half the picture. The underlying composition may have several writers and publishers, each holding different shares in different territories, and that information often lives in separate systems that were never designed to talk to each other.
Rights data is the weakest link
Ownership doesn’t stand still. Catalogs change hands, publishing deals expire, territories get carved out, and splits get disputed. Each change has to reach every system that pays on that work. When it doesn’t, two parties end up claiming the same share, and payments sit on hold until someone resolves the conflict by hand.
The fix is to treat rights data as a living, versioned record of who owned what, where, and as of what date. Without that history, a company can calculate a payment but can’t prove it was right. Proof is exactly what artists, auditors, and catalog buyers increasingly expect.
Transparency is an architecture decision
Today, you cannot bolt transparency, or intelligence, onto a batch-processing system built for yesterday. Most royalty engines were designed to close the books on albums, sold in units, a few times a year. They were never meant for a world of continuous, global, multichannel micro-consumption across more than 60 territories, each with its own rules, currencies, and languages.
A modern royalty pipeline works differently. It ingests usage at the event level rather than in quarterly summaries. It normalizes and matches that usage against a single source of truth for identifiers and ownership. It applies contract rules and splits automatically, reconciles across every incoming source, and settles payments with full lineage. That lineage matters most, because it lets anyone trace a line on an artist’s statement back to the streams that produced it. Without lineage, a statement is a claim. With it, the statement becomes proof.
When a global music leader rebuilt its royalty platform recently, the headline was a 3x performance gain. The more telling detail was how they got there: a cloud-native, API-first, microservices architecture that spun up new environments in minutes instead of weeks, and a data model rebuilt so artists could finally see, in near real time, how their earnings were made. Transparency became possible only when the architecture changed.
Trust is a function of latency. The shorter the time between a stream happening and an artist understanding it, the more trust the system holds. Legacy stacks make that latency structural. Modern ones make it a design choice.
The coming explosion nobody is sizing
The number of payable royalty events is about to increase by orders of magnitude. Think about where consumption is heading: per-second sync placements, sampling micro-splits, fan-platform microtransactions, short-form clips, licensing where a rights holder is paid for influence rather than a clean master. Each of these fractures a single royalty line into hundreds or thousands. That one viral snippet wasn't an anomaly, but a preview. Luminate counted 5.1 trillion global streams in 2025, up nearly 10% from the year before, and close to 150,000 new tracks now land on streaming platforms every day. The industry is quietly moving from thousands of payable events per release to billions of micro-events across a catalog.
This is not a legal problem. It’s a data engineering problem of scale, reconciliation, and settlement, and most back offices are nowhere near ready. The companies that win the next five years will be the ones whose ledgers can physically keep up.
From back office to platform business
Here is where the story turns. Once royalty data is clean, connected, and flowing in near real time, the same platform that pays artists can start predicting for them. Machine learning trained on consumption and rights data can forecast revenue, surface which tracks and territories are about to move, and value assets with far greater confidence. The royalty platform stops being an accounting engine and becomes a predictive intelligence platform.
That is a different kind of company. It forecasts revenue, so advances and marketing spend are smarter bets. It values catalogs on evidence rather than estimates. It launches new products and licensing models faster, because the data foundation is already there. And it earns trust across creators, partners, and investors, because everyone is finally looking at the same reliable numbers.
This is why it matters far beyond any single statement. Billions of dollars in catalogs have changed hands, with private equity now a structural force in how rights are priced, and those valuations rest largely on royalty data. A catalog with clean, forecastable data is simply worth more than one whose earnings are a quarterly guess, because a buyer can see exactly what they are paying for. The industry’s next competitive advantage won’t come from owning content. Everyone owns content. It will come from turning rights, royalties, and consumption data into real-time intelligence the rest of the business can act on.
So, let’s go back to that songwriter, phone still buzzing. The next era of music won’t be defined by who creates the next hit, but by who can account for it and who can turn that accounting into foresight. In an industry built on creativity, trust will increasingly be earned through data and platform engineering.
[Editor's note: This is a contributed article from Brillio. Streaming Media accepts vendor bylines based solely on their value to our readers.]
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