As landmark deals near, record labels push streaming-style payments and attribution tech to govern how AI trains on — and generates — music

A template for training data — and AI-generated tracks

Universal Music Group and Warner Music Group are weeks away from signing what industry executives describe as landmark artificial-intelligence licensing agreements — a turning point that could define how technology companies pay for access to the world’s most valuable song catalogs. According to people familiar with ongoing talks reported by the Financial Times and Reuters, the labels are hashing out terms with a mix of Big Tech platforms and fast-growing AI audio startups. The goal: bring AI training and AI-generated tracks inside the music industry’s licensing system rather than leaving them in a legal gray zone.

The prospective deals follow a turbulent year in which AI tools capable of mimicking artists’ styles flooded social platforms and streaming services. Startups such as Suno and Udio have been accused by labels of ingesting commercial recordings without permission; platforms including Spotify and Deezer, meanwhile, have wrestled with a surge of synthetic or ‘spammy’ uploads. Now, instead of battling on every front, the majors are seeking a template: a predictable way for AI developers to pay for training data and for any AI outputs that rely on copyrighted music.

Who’s in the room

People involved in negotiations say the labels are pushing two pillars. First, a streaming-style payment model so that every use of a song — whether for model training, inference, or an AI-generated clip — triggers a micropayment. Second, verifiable attribution: technical systems that can identify when a model has learned from, or an output meaningfully resembles, a particular recording or composition. Think of it as a Content ID for the AI era, a mix of audio fingerprinting and usage logs that can be audited.

Talks span an unusually broad roster. On one side are the catalogs controlled by Universal and Warner — home to global stars across pop, hip-hop, and catalog rock. On the other side are AI-native audio companies such as ElevenLabs, Stability AI, Suno, Udio and Klay Vision, alongside platforms with immense distribution power, including Google and Spotify. The logic is straightforward: training models in the clear and clearing outputs at scale become far easier — and safer — if the biggest rightsholders agree on the baseline rules.

Why the urgency

Timing matters. The business of streaming has matured, growth is slowing, and labels are hunting for the next dependable revenue line. AI offers both a threat and an opportunity. Left unlicensed, it risks diluting the value of recorded music and confusing fans about what is ‘real.’ Licensed properly, AI could unlock paid developer access to catalogs, new creator tools for artists, and a long tail of micro-uses that add up. For AI companies, the appeal is certainty: clearer rights reduce legal risk and ease fundraising.

What artists want

Artists and songwriters are watching for two protections. One is consent and control — opt-in and opt-out mechanisms for voice cloning and style emulation, plus a veto over endorsements or artist likeness. The other is fair split accounting: if an AI output uses stems or resembles a particular recording, who gets paid and how much? Executives involved in the talks say early frameworks would route money to master and publishing rightsholders first, then flow through to contracts — but they acknowledge that voice models and style transfer raise questions traditional deals weren’t designed to answer.

The tech to make it work

The technical hurdles are non-trivial. Fingerprinting a finished track is one thing; proving that a neural network was materially influenced by a specific recording during training is another. Labels are urging partners to deploy auditable datasets, watermarking where possible, and robust logging so that usage events can be reconstructed. Some companies are exploring ‘consented corpora’ — curated, paid libraries segregated from broader web-scraped data — to avoid contaminating models with unlicensed works.

Enforcement, labeling and provenance

Enforcement will hinge on platform behavior. Even with licenses, the majors will expect Spotify, YouTube, TikTok and others to police uploads that impersonate living artists or mislead audiences. The emerging consensus is that AI music needs visible provenance: labels want clear labeling for synthetic tracks, alongside takedown pathways when outputs cross legal or ethical lines. Expect the first licenses to tie continued access to compliance metrics and audit rights.

What this means for fans

For listeners, the most immediate change may be behind the scenes: more AI-powered features inside music and video apps — smarter search, on-the-fly remixes authorized by rightsholders, and personalized stems for karaoke or fitness. Over time, fans should see clearer ‘made with AI’ disclosures and fewer whack-a-mole takedowns. If the economics work, artists might also release official AI voice packs or co-create with fans under revenue-sharing terms.

Competitive ripple effects

Universal and Warner moving first could pressure rivals to follow, particularly if early partners tout lower legal risk and fast innovation. Sony Music has publicly emphasized ethical AI and artist consent; independents are likely to negotiate collective frameworks so that smaller rights holders aren’t left behind. The majors will also compete with one another on product; expect label-branded tools, sandboxed datasets for developers, and preferred partnerships with platforms that deliver the best attribution and payouts.

Unanswered questions

Plenty remains unsettled. How will rates be set for training versus generation? Will voice models require separate consent from performers whose contracts didn’t contemplate cloning? Can detection keep up as models grow better at style transfer? And how will money flow to background vocalists, session musicians and non-featured contributors when AI outputs are composites rather than covers? The first wave of deals won’t answer every question, but they’re a start.

The bottom line

If the agreements close as expected, they will mark the industry’s most consequential shift since streaming. They won’t stop unlicensed models overnight, but they could create a center of gravity: a way for legitimate players to pay, experiment, and compete without trampling creative rights. Just as the early iTunes and Spotify deals rewired digital music, licensing AI’s inputs and outputs could define the next decade of how songs are made, shared and monetized.

Key Takeaways

Labels are pushing streaming-style micropayments for both AI training and generation.

Attribution and auditability — a ‘Content ID for AI’ — are central to the framework.

Deals under discussion span startups (e.g., Suno, Udio, ElevenLabs, Stability) and platforms (Google, Spotify).

Artists seek consent controls for voice/style and clear revenue splits for AI-derived outputs.

The first licenses won’t end unlicensed training, but they could set commercial norms fast.

Reporting based on public statements and media reports as of publication.