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‘Artificial Intelligence’ is no longer a theoretical technology hovering on the horizon, but is quickly (and with ever increasing speed) being embedded into everyday workflows- powering products and increasingly shaping entire industries. For the music business, as for every other sector, the question is no longer if AI will matter but how it is being applied in practice today- and where it is likely to drive competitive advantage tomorrow.

Imagine trying to value a ring in a jewellery store, but wearing a blindfold. You can sense the outlines, feel the cut of the stone and setting, but the fine detail- the information that actually determines whether you’re about to buy a diamond or a dud- is obscured. That’s where many funds still find themselves today. Investment decisions are often made with incomplete or unreliable data. Acquisition packs are full of disparate (and static) spreadsheets

The music publishing industry is no stranger to disruption. Every year seems to bring a new wave of technological, economic, or cultural change that evolves how music is consumed, and subsequently licensed and monetised. Keeping a keen eye on the data for areas of potential growth provides rights holders with a super power. Seeing what opportunities are developing, at what rate, and what the uplift is likely to look like as the revenue converts down the pipeline- particularly

The music industry has never been short on creativity- but in the smaller Publishing niche it’s often been sadly short on collaboration. Not between songwriters, producers, or artists- but between the organisations, systems, and standards that underpin how the business actually serves these creators. For an industry built on relationships, too much of our data and infrastructure operates like a walled garden.

Books like All You Need to Know About the Music Business (Don Passman) or Music: The Business (Anne Harrison) and other various law primers have certainly become the ‘go tos’ for a reason. Though undoubtedly useful for understanding contracts, rights, and royalties at a granular level, they are also relatively dense as they are so granular.

The conversation around “independence” in the modern music industry has come to the fore in recent weeks, and is getting harder to define. The major music companies have always built to consolidate power and position- not just through powerful content ownership, but via distribution and now through data.

We’ve all had that feeling. You suddenly hear a new song on the radio. A friend mentions it. Then it pops up in a reel, a TV ad, a shop playlist... suddenly, it’s everywhere. But somewhere along the way, without even realising it- you start to like it. Maybe even love it. You Shazam it. Save it. Play it again later. It becomes your go-to. You don’t quite know how it happened… but it did.

After data (which, have no fear, is going to feature) the economic landscape for music publishing in a digital world is one of my favourite topics to explore. Well… alongside licensing frameworks, systemic politics, global society pipelines- which are all, of course, different facets of the same dynamic. Whichever way you look at it, songs don’t receive value on par with what’s shared by the rest of the industry. And even when value is ascribed, it’s struggling to get through

Art has a fine line to navigate- a continuum where defining itself has far reaching implications- from the law to the economy. In almost every era of history, the same debate has resurfaced in music: art, or business? Music is expression, storytelling, and ‘soul’. It is connectivity and communication that crosses borders and languages- transcending individuals, able to curate emotion, to create community and even manifest radical action. The romantic answer is “art,” of co

The pace of change is accelerating. This week we released a new, free tool on the Fix Music website: a clean, simple way to retrieve recording metadata- including ISRCs, artwork, release info and more- from any Spotify link, in downloadable bulk format. No login. No fee. No strings. It’s already helping users save time and get what they need, fast. And… it was entirely built by AI.

That’s right. Another newsletter about data in the music industry. It’s a hill I’m willing to die on- that data is the critical lifeblood of the entire ecosystem, and that those who grasp this the quickest will be the ones who accelerate their businesses the fastest.

There’s never been a better time to be a global music fan. Korean pop groups dominate the Billboard charts. Latin megastars headline the world’s biggest festivals. Afrobeats is on everyone's playlists. A user in Jakarta can stream a Nashville singer-songwriter seconds after their release… music’s reach is truly borderless.

The Major record labels and two of the most prominent generative music platforms, Suno and Udio, have reportedly moved from trading lawsuits to negotiating licenses. These generative AI platforms were(/still are) facing litigation for using copyrighted music to train their models. Now they’re sitting at the table with the very same rights holding companies, working out deals that will both legitimise and monetise their models.

Institutional investment has aggressively been reclassifying music as an ‘asset class’. But what happens when art and capital collide?

We’ve been exploring the MLC data since 2021. It’s not the only dataset we use at Fix, but it’s certainly one of the more fascinating. Here are five things the MLC data tells us that every publisher should know.

Metadata is the oil that keeps the Music Publishing engine running. It defines what’s registered, what’s matched, and ultimately, what (and who) gets paid. But unlike your typical crude oil, rights data isn’t fungible or easily traded- it’s locked in silos, guarded as proprietary, and scattered across a network of databases and gatekeepers.

In music publishing, advances have long been only the headline number. Over time, terms and models have received scrutiny and subsequently shifted. Gone are the days of 50/50 deals for life of copyright, now supplanted by profit-shares and “at source” accounting. Beyond the terms laid out on paper, creators presently have far more contextual variables to assess. Likelihood of sync placements is one by example- a factor so heavily based on historic performance that is has n

AI is clearly having a moment. Photo by Possessed Photography From image generation to songwriting tools, the emergence of generative AI has sparked widespread debate in the creative industries. In music publishing, much of the discussion has understandably centred around authorship, copyright, and how to safeguard the value of human creativity in a world where machines can mimic it. But that’s only one side of the story. If we zoom out and look beyond the courtroom, AI has t

100,000+ recordings released and 10,000+ songs registered per day. Is this an opportunity, or a data nightmare?