Challenges of AI Adoption for Music Labels

🎵 An AI-generated song just hit #1 on Billboard. What does that mean for the future of music? “Walk My Walk” — by Breaking Rust — became the first fully AI-created track to top Billboard’s Country Digital Song Sales chart. No human singer. No studio sessions. No lived experience. Just an algorithm. This isn’t just a music story — it’s a business story. If AI can write, sing, produce and release a chart-topper: 💡 What happens to the economics of the music industry? 💡 How do record labels justify million-dollar artist investments when an AI can create infinite “artists” at near-zero cost? 💡 Who owns the royalties — the coder, the model, or no one? 💡 Will audiences care if the song emotionally moves them anyway? For the industry, this signals 3 major shifts: 1️⃣ Cost model disruption – AI can produce music faster and cheaper than human creators. 2️⃣ New talent definition – The next “hit maker” may be a machine, not a musician. 3️⃣ Ethical + legal grey zones – Copyright, transparency, and authenticity will become battlegrounds. But there’s opportunity too: ✔ Human-AI co-creation will unlock entirely new genres ✔ Independent artists can produce studio-quality music without big budgets ✔ Labels can build virtual artists and micro-target audiences at scale The big questions are: * What does it mean to be an “artist” in an age where identity can be generated, not lived? • How should the music industry balance innovation (AI art) with protection of human artists’ livelihoods? • What role should platforms (Spotify, YouTube) play in labeling or regulating AI-generated music? • How do we ensure that AI-generated music remains diverse and culturally inclusive, rather than homogenized? #AIMusic #FutureOfMusic #MusicIndustry #ArtificialIntelligence #CreativeEconomy Devraj Sanyal Jay Mehta Would love your views and inputs 🙏 Check out the song if you haven’t already : https://lnkd.in/dsegspCg

The majors once called Suno and Udio “mass infringers.” Now they’re asking for royalties and equity.  In less than a year, Universal, Sony, and Warner went from courtroom threats to quiet negotiations, asking the same AI companies they sued to license their catalogs… with fingerprinting systems, revenue shares, and commercial vetoes baked in (my new piece for Forbes). But here’s the real story: These aren’t just settlements. They’re blueprints for the future of music licensing, one that could lock in rules before most artists even realize the game has changed. Fingerprinting tech, attribution promises, opt-outs (maybe), it all sounds familiar. So does the risk: creators being “included” without consent, and monetization frameworks shaped by those already at the table. The labels want attribution tech “like Content ID.” They want to approve new AI features. And they want equity. And what about Artist-level licensing, direct opt-ins or opt-outs for creators and visibility on how AI models are trained on underlying compositions or lyrics? As CISAC’s Gadi Oron bluntly put it: “Negotiating solely with the majors will not provide the full set of rights required. Labels only control the masters.To use music lawfully, especially for training or generating new content, AI companies also need to obtain rights to the underlying compositions and lyrics managed by CMOs". And as Future Play Music’s Loredana Cacciotti warned: "We’re heading into déjà vu—again."  I spoke to CISAC’s Gadi Oron, Future Play Music’s Loredana Cacciotti, the Sureel AI team (Tamay Aykut, Benji Rogers Michael Pelczynski), Cosynd’s Liz Cimarelli, and many others about what’s really at stake, and why we’ve seen this movie before. Let's talk about: - The timing (regulatory shifts, investor pressure, looming EU/UK crackdowns) - The tech (why “attribution” is the new battleground) - The risks (creators sidelined in deals built on their work) - And five urgent questions no one’s answered yet: royalties, rights layers, compulsory licenses… and who gets paid when equity is on the table. This isn’t just about Suno or Udio. It’s about who gets to shape the future of music in the AI era, and who gets left watching from the sidelines. What Suno And Udio’s Licensing Deals With Music Majors Could Mean For Creators’ Rights: My new article for Forbes https://lnkd.in/g33SsQUY #AI #MusicIndustry #Copyright #GenerativeAI #MusicLicensing #CreatorEconomy #Suno #Udio #Attribution 

Spotify deleted 75 million AI generated songs last year That’s 1 in every 3 songs There’s a flood of AI music   Cloned voices, AI-written beats, and “fake” tracks uploaded faster than labels can react. Now Universal and Warner Music (homes to Taylor Swift, Kendrick Lamar, Coldplay, and more) are closing in on the first landmark licensing deals with AI companies. The idea is simple but massive: - Every time AI systems use or generate music, artists get paid - just like streaming royalties today. - AI companies must build tech to detect when copyrighted music is used, similar to YouTube’s Content ID. For the labels, it’s a chance to avoid repeating the Napster era, when music piracy wiped out more than 60% of the industry’s value. For artists, it’s the first real shot at being compensated in a world where their voices and sounds can be cloned in seconds. The AI revolution won’t kill music - but it will force the industry to rewrite the rules of ownership and payment. The ones who adapt fastest will decide what the future of music looks like.

Major record labels & Spotify are frenemies working together to prevent AI music from competing with traditional artists, and here's why they do it: Artist Solidarity Say what you will about the relationship between artists and labels, labels need strong artist brands and great songs to run their business. They might sign onerous deals with individual artists, but they want to protect the community they rely on. Therefore, they will push Spotify and other streaming services to prioritize "real music" made by "real artists" over purely AI created content. Spotify's hosting bill TL;DR, it's high. Growing at 100K+ songs daily. Any excuse to lower "dead stock" is good for their margin. AI music is any easy target because it's easy to ID and block (lots of tools for this) and doesn't align with artist or industry interests. Royalty Pool Dilution The music royalty ecosystem is a finite pool of money distributed to artists based on streams. Major labels want the majority and have leverage over Spotify to prioritize their music since streaming services rely on popular artists for user retention. This creates a shared incentive to limit lower end of independent music from getting paid, hence the recent two-tier announcement. (Note that at the same time Spotify also increases the visibility established indie artists who get decent streams since it pays lower royalty rates to indies.) Market Share Payouts Did you know that YouTube and other platforms pay the majors and Merlin for any misidentified content (black box) on a market share basis? The more of the pool a label gets via its artists (its total market share %) the more mystery box money they get too. Naturally, anything diluting their total share also lowers their black box share which makes it a threat. Quality Control Let's be real, without an artist sweating over every aspect of a song the result is often thoroughly mediocre. It's also not as fun to listen to songs without knowing the story, what that song meant to them, why they wrote it and so on. While some AI music proponents argue that this is about democratizing music, the best art is intentionally crafted with the blood, sweat and tears of the artist. You can feel it in the music. My take... I don't personally disagree with any of this even as a founder building a generative music product (Tuney) because I think the opportunity is to enable artist creativity through tools instead of replacing it completely and letting "anyone be a musician". I still think the best artists will use these tools, and contribute their effort and creativity in a way to make their music stand out. Those who want a lazy way of making quick music without going through the arduous artist journey don't need exposure to the same revenue opportunities as the artists who make music their life's work. They can make it and share it socially, but I don't see a need to officially release it to streaming services.

Last week at Water & Music, we revamped our free newsletter, which will feature a new essay from me every month on the music-tech industry's most pressing issues. My first installment, linked below, is on music AI licensing. Fun fact: Nearly all of our active consulting projects right now are related to music AI. And out of those AI projects, the majority are concerned specifically with the relationship between AI and music rights. While this was not by design, it certainly fits the moment. The music AI licensing landscape is shifting dramatically in real time: Major labels are reportedly discussing settlements with Suno and Udio, while ElevenLabs just launched a fully licensed music model with Kobalt Music, Merlin, and SourceAudio on board. After years of standoffs and litigation, commercial partnership precedents are finally emerging. Yet when we speak with rights holders outside the major label ecosystem about the potential AI licensing opportunity, their response is essentially a giant ¯\_(ツ)_/¯ Should I even license? To whom? For how much? For most music rights organizations, these questions about AI's commercial opportunity remain unanswered. And the frameworks being hammered out at the top aren't translating to actionable guidance for everyone else. After months of advising both sides, we've distilled the complexity down to three fundamental questions. Get these right, and the path forward becomes much clearer: 💡 What's the actual use case? (Stem separators vs. Suno = completely different ballgame) 💡 What data do developers really need? (Hint: probably not your entire catalog) 💡 What are the incentives — and how long will they last? (Synthetic data and open-source models are flipping the power dynamic) Full essay in the link below. Would also love to hear what's happening in your corner of the industry: Are you seeing the same dynamics? What other questions are you grappling with around AI licensing? #musicindustry #musictech #musicAI #musicbusiness #musiclicensing

With AI-generated music on the rise, crucial questions emerge from its impact on music quality to the ethical dilemma of training models on copyrighted material, essentially creating competitors to original works. The issue is, in fact, twofold: copyrighted music might be used to train AI systems, and on the other hand, the generated music can mimic the voices of famous singers. How will the music sector respond? Will they be the vanguard in asserting their rights? The solution again lies in finding a delicate equilibrium. While AI music broadens creative horizons and supports innovation across diverse fields, it must not come at the expense of artists. Striking a balance demands proactive measures to safeguard creators' rights while leveraging AI's potential for artistic expression. Solutions must emerge that honour creativity and intellectual property.   The EU AI Act will require generative AI providers to publicly disclose details of copyright works used in training, but there are serious doubts that this will be enough to solve this question, further legislation might be necessary soon to provide adequate protection to IP rights in the age of artificial intelligence.   What do you think, which strategies could help AI developers ensure compliance, considering the challenges posed by training on vast datasets of copyrighted material? In this evolving landscape of AI-generated music and artists' rights, how can we ensure that innovation thrives without compromising the integrity of artistic creation and the rights of creators? https://lnkd.in/dN2gHbUz #ai #ailaw #innovation #ip