MBW Views is a collection of op-eds from eminent music trade individuals… with one thing to say. The next MBW op-ed comes from Andreea Gleeson, former CEO of TuneCore and founding father of AGA (Andreea Gleeson Advisory), the place she advises firms and buyers on development, innovation, and strategic transformation throughout music, media, expertise, and the creator economic system.
Right here, Gleeson argues that AI’s greatest problem isn’t the expertise itself, however constructing the interoperable business infrastructure wanted to make sure creators are correctly credited, compensated, and guarded.
Over the previous few months, the music trade has quietly crossed an necessary threshold. Not one other lawsuit. Not one other congressional listening to. Not one other debate about whether or not AI is a menace or a possibility for music. As a substitute, we’ve entered the commercialization section of AI.
In simply the final a number of weeks, Deezer introduced that greater than 90,000 AI-generated tracks at the moment are uploaded each day, representing over half of all new uploads to its platform. TIDAL introduced it’s going to routinely determine absolutely AI generated recordings and exclude them from royalty bearing streams. The worldwide report trade has proposed standardized AI labels for streaming platforms.
IFPI has additionally rolled out chart eligibility ideas throughout its international community of official music charts, utilizing these AI labels to find out how AI Assisted and AI Generated recordings will qualify for chart inclusion. Spotify and Common Music Group together with Merlin unveiled licensed AI instruments that permit followers to create approved covers and remixes from taking part artists. In the meantime, Congress continues advancing the bipartisan No Fakes Act to guard voice and likeness.
Considered individually, these bulletins could appear unrelated. Collectively, they level to one thing a lot larger: the business guidelines for AI music are already being established. If historical past is any information, these guidelines will form the trade lengthy earlier than laws catches up.
We’ve seen this film earlier than
Spotify basically modified music consumption 10 years earlier than the Music Modernization Act turned legislation in 2018. YouTube‘s launch of Content material ID in 2007 equally remodeled one of many trade’s greatest copyright challenges into one in all its most necessary attribution and monetization methods, years earlier than policymakers absolutely understood the implications of person generated content material. In each instances, {the marketplace} standardized business fashions first. Regulation adopted.
AI seems to be following the identical path.
The subsequent chapter received’t be outlined by the expertise itself. It will likely be outlined by the infrastructure we construct round it and whether or not that infrastructure correctly credit, protects, and pays creators.
My perspective comes from spending greater than a decade at one of many music trade’s key business crossroads: distribution. After I was CEO of TuneCore, I labored carefully with DSPs, labels, creator instruments and expertise companions to assist unbiased artists convey their music to market. Sitting on the distribution layer gave me a singular vantage level into how lacking info upstream typically translated into missed attribution, misplaced monetization and fewer alternatives downstream. Over the previous three years, I additionally labored alongside many of those identical firms as they started experimenting with AI, offering a entrance row seat to how immediately’s business frameworks have began to take form.
I skilled that shift firsthand in 2023, when generative AI first burst into public consciousness and uncertainty dominated almost each dialog. On the time, I partnered with Grimes by way of TuneCore to launch one of many first frameworks for responsibly distributing AI collaborations. Her proposal was remarkably easy: creators may use her AI voice mannequin, however solely along with her permission and provided that revenues have been shared. Moderately than rejecting AI, the framework established ideas that proceed to underpin lots of immediately’s business discussions: consent, management, compensation and transparency.
Wanting again, what strikes me most isn’t that the framework answered each query. It didn’t. It’s that the trade didn’t look forward to laws earlier than starting to experiment. Artists have been already exploring AI as a artistic instrument. Know-how firms have been constructing merchandise. Distributors have been growing insurance policies. Platforms have been adapting their enterprise fashions. The market began fixing issues whereas lawmakers have been nonetheless defining them, and lots of of immediately’s most important developments proceed to mirror those self same underlying ideas.
Shoppers Are Sending a Equally Nuanced Message Too
Earlier this 12 months, Luminate‘s Generative AI in Music report discovered that general curiosity in AI generated music declined from a web unfavorable 13 % in Could 2025 to unfavorable 20 % by the tip of the 12 months, with the sharpest decline amongst Gen Z and Gen Alpha. However Luminate’s newest 2026 Midyear Report and their AI & Media: Viewers Attitudes deep dive counsel the dialog is turning into extra refined. Moderately than rejecting AI outright, customers are differentiating between AI that enhances human creativity and AI that replaces it. One in three U.S. music listeners say they’re comfy with AI creating music instrumentals, whereas 46 % are uncomfortable with AI creating a completely new music carried out by an AI voice.
The identical report discovered that creators are embracing these instruments extra readily than most of the people. 54 % of U.S. musicians report optimistic emotions towards AI music instruments, in contrast with 35 % of non musicians, and 18 % already use AI to edit or remix present music. Collectively, the findings counsel customers and creators aren’t rejecting AI. They’re asking for transparency, authenticity and human company whereas embracing new methods of making, collaborating and taking part with music.
These two alerts, the trade’s fast experimentation and customers’ rising demand for transparency, are starting to converge. Collectively, they level towards the following problem: how the business infrastructure round it must be constructed. The reply begins by recognizing that AI isn’t a single expertise or a single market. It’s an interconnected worth chain.
The 4 Interconnected Layers of the AI Music Worth Chain
If AI is getting into its business period, it’s necessary to acknowledge that no single firm or expertise will outline it. As a substitute, commercialization is taking form throughout 4 interconnected layers of the AI music worth chain. The primary is creation, the place music is made. The second is distribution, the place music enters the business market. The third is attribution, the place provenance, transparency and possession are established. The fourth is consumption, the place streaming platforms decide discovery, labeling and in the end monetization.
Every layer depends upon the one earlier than it. Data captured throughout creation in the end influences every part downstream, from attribution and royalty funds to client belief. AI by way of this lens shifts the dialog away from particular person merchandise and towards the infrastructure that can in the end decide how worth flows by way of the music ecosystem.
One of many greatest misconceptions about AI is that it primarily encourages alternative. More and more, we’re seeing the alternative. It encourages participation. A number of years in the past, MIDiA Analysis predicted that music would evolve from static music to dynamic music, the place followers don’t merely devour songs however actively work together with them. That future is already starting to emerge.
Considered one of my favourite examples comes from legendary Chicago home vocalist Robert Owens. Moderately than treating AI as one thing to worry, Owens partnered with Voice-Swap, Beatport and LabelRadar to ask producers and creators around the globe to create music utilizing his licensed AI voice mannequin. The objective wasn’t to impersonate him. It was to collaborate with him. The profitable entries weren’t celebrated as a result of they fooled listeners into believing Robert Owens recorded them, however as a result of they expanded what collaboration between artists and followers may appear to be.
Spotify’s not too long ago introduced partnerships with Merlin and Common Music Group to allow licensed AI covers and remixes from taking part artists and songwriters takes this concept one step additional. It productizes the very habits MIDiA envisioned years in the past of a bifurcated market, making a business framework the place fan participation could be licensed, monetized and shared. In some ways, it echoes YouTube’s introduction of Content material ID. What initially appeared disruptive in the end turned one of many trade’s largest monetization methods as a result of the correct business infrastructure was constructed round it. AI has the potential to observe an identical path, not by changing artists, however by creating new methods for artists and followers to create worth collectively.
That brings us again to the primary layer of the worth chain: creation.
A lot of immediately’s dialog focuses on AI detection, and for good cause. Detection applied sciences have gotten more and more refined, serving to distributors and streaming platforms determine AI generated recordings, defend rights holders and enhance belief throughout the ecosystem. However detection has an inherent limitation: it begins after the music has already been created.
Think about serving a fancy meal to a chef and asking them to determine each ingredient and each step used to organize it. An skilled chef would possibly come remarkably shut, however they’re nonetheless reconstructing the recipe after the very fact. Now think about the sous chef writing down the recipe because the meal is being ready. Each ingredient, each measurement and each substitution is documented because it occurs. That’s the distinction between detection and provenance.
“That is the place digital audio workstations, or DAWs, grow to be some of the neglected items of the AI ecosystem. AI is now not confined to standalone functions. It’s more and more embedded straight into skilled artistic workflows by way of vocal modeling, stem separation, mastering, songwriting help and different manufacturing instruments.”
That is the place digital audio workstations, or DAWs, grow to be some of the neglected items of the AI ecosystem. AI is now not confined to standalone functions. It’s more and more embedded straight into skilled artistic workflows by way of vocal modeling, stem separation, mastering, songwriting help and different manufacturing instruments. As AI turns into a part of the artistic course of, DAWs grow to be the best place to seize trusted provenance. Moderately than asking downstream detection methods to estimate whether or not AI was used, the software program itself may securely doc which AI instruments have been used, what was human carried out and even confirm when no AI was used in any respect.
Consider it just like the natural sticker on a banana. Shoppers don’t examine the fruit and guess whether or not it’s natural. They belief a certification system that adopted the product from its origin. Music might in the end require one thing related, not as a result of listeners want technical metadata, however as a result of belief more and more depends upon verifiable provenance.
Metadata Turns into Cash
That distinction is turning into more and more necessary as AI labeling begins influencing business outcomes. TIDAL’s current resolution to determine absolutely AI generated recordings and exclude them from royalty bearing streams demonstrates that AI classification is now not merely informational; it’s turning into financial. On the identical time, the trade is exploring standardized AI labels throughout streaming platforms, an necessary step towards larger transparency.
IFPI has additionally launched chart eligibility ideas throughout its international community of official music charts that use AI labels to find out how AI Assisted and AI Generated recordings qualify for chart inclusion. Chart eligibility extends effectively past trade recognition. It influences visibility, promotional alternatives, client discovery, and a variety of downstream business advantages that usually accompany chart success. As AI labels start informing each monetization and chart eligibility, the accuracy of the underlying metadata turns into more and more consequential.
However labels alone are solely the ultimate output. With out trusted provenance upstream, labels stay declarations fairly than verifiable info. Who supplied the knowledge? Was the AI mannequin licensed? Did the artist consent? How a lot of the recording was AI generated? As AI labeling begins influencing royalties, licensing, advice methods and client belief, these questions grow to be more and more necessary.
Happily, lots of the constructing blocks exist already. The MIDI Affiliation’s work round MIDI 2.0 factors towards a future the place artistic instruments, distributors, detection applied sciences and streaming platforms alternate standardized provenance all through the lifetime of a music. Creation metadata flows into distribution. Distribution informs attribution. Attribution powers labeling. Labeling helps monetization. The worth chain turns into related.
That’s the reason I imagine AI is quickly turning into much less of a copyright problem and extra of an interoperability problem. Detection applied sciences will stay important for validating provenance and figuring out unhealthy actors, however the strongest ecosystem will mix verified info captured at creation with unbiased verification downstream. Collectively, these methods create one thing the music trade has traditionally struggled to realize at scale: confidence. Confidence that artists obtain correct credit score, rights holders obtain correct cost, customers perceive what they’re listening to, and AI can broaden creativity with out eroding belief.
From Innovation to Coordination
The encouraging information is that the trade doesn’t have to begin from scratch. Throughout each layer of the AI music worth chain, significant work is already underway. Streaming companies are growing new approaches to AI transparency and monetization. Labels are negotiating licensing frameworks with AI firms. Distributors are establishing insurance policies round AI submissions. Detection firms proceed advancing attribution applied sciences. Requirements organizations like The MIDI Affiliation are constructing interoperability frameworks, whereas legislators proceed pursuing protections such because the No Fakes Act.
The problem is now not innovation. It’s coordination.
Every of those initiatives addresses an necessary piece of the puzzle, however none can set up a related AI ecosystem by itself. Provenance captured throughout creation has restricted worth if it can’t stream seamlessly by way of distribution, attribution and in the end monetization. The subsequent section requires connecting these efforts into shared business infrastructure fairly than persevering with to construct them in parallel.
One promising instance is the Music Tech Coalition initiative being spearheaded by Peter Brown of Venable. As Peter shared with me not too long ago, “Moderately than changing present work, the Coalition’s objective is to attach it, bringing collectively platforms, labels, distributors, expertise firms, requirements organizations, commerce our bodies and policymakers to align round sensible interoperability. This isn’t simply concerning the technical requirements and agreements that exist, however about trade leaders keen to information the way it all works collectively and help implementation throughout the ecosystem.”
“The subsequent chapter received’t be outlined by one AI mannequin, one lawsuit or one piece of laws. It will likely be formed by the methods we construct between creators, artistic instruments, distributors, attribution applied sciences and platforms.”
Maybe the clearest signal that the trade is prepared for this dialog comes from the current A3E survey, commissioned by Venable. Practically 89 % of respondents imagine the trade lacks adequate coordination round interoperability, transparency and belief. Greater than 92 % expressed curiosity in taking part in future coalition discussions, with metadata requirements, provenance and interoperability rising as the very best priorities.
These findings reinforce what I’ve noticed all through the previous a number of years. The trade isn’t debating whether or not belief issues. It’s more and more aligned on methods to construct it.
If the previous twenty years have taught us something, it’s that the best alternatives in music typically come from constructing shared infrastructure. Streaming didn’t succeed due to licensing agreements alone. It succeeded as a result of a complete ecosystem advanced round frequent business frameworks. Content material ID wasn’t merely a expertise. It turned an trade customary for attribution and monetization.
AI now presents the trade with an identical alternative.
The subsequent chapter received’t be outlined by one AI mannequin, one lawsuit or one piece of laws. It will likely be formed by the methods we construct between creators, artistic instruments, distributors, attribution applied sciences and platforms. The businesses that create the best long run worth might not be these with probably the most superior AI, however people who assist set up the trusted infrastructure by way of which AI can scale responsibly.
Congress will finally write legal guidelines. However the business foundations of AI music are being constructed immediately.
The chance earlier than us is to make sure these foundations are interoperable, clear and artist centric. If we get that proper, AI doesn’t need to grow to be a race to the underside. It will probably grow to be the catalyst for a extra collaborative, economically sustainable music ecosystem, one the place artists are correctly credited, pretty compensated and empowered to take part within the subsequent period of creativity.
Music Enterprise Worldwide
