Photo by Chen on Unsplash The only acceptable stack is a Katstack

If you were to compile many of this GuestKat’s posts over the last few months, it wouldn’t surprise me if the famous Charlie Day Conspiracy Meme** **sprang to mind. Many of these posts centre on agreements struck between music publishers, platforms and AI companies. Agreements that will shape future legislation through the back-door: private ordering.

However, the first agreement of 2026 strikes a different tone. Universal Music Group (UMG) has announced that it has entered into an agreement with NVIDIA to

pioneer responsible AI for music discovery, creation, and engagement [that] leverages NVIDIA AI infrastructure and UMG’s industry-leading music catalogue comprising millions of tracks covering every genre and era.

The agreement centres upon Music Flamingo Model, a ‘novel-language model, designed to advance music (including song) understanding in foundational audio models’. NVIDIA explain that prior models were restricted to ‘short, high-level captions, answering only ‘surface level questions, and showing limited generalizations across diverse musical cultures.’

Music Flamingo draws from a ‘large-scale dataset’ comprising ‘rich captions and question–answer pairs covering harmony, structure, timbre, lyrics, and cultural context’ to create a new standard for advanced music understanding. Allegedly it means that eventually ‘next generation of models [will] engage with music as meaningfully as humans do’. The agreement foresees ‘revolution[ary] music discovery’, ‘enhance[ed] fan engagement’, and the empower[ment] of artists with creation tools’. All under the façade of facilitating ‘responsible AI innovation’, this Kat (again) suspects something afoot.

A new AI copyright rhetoric

Sir Lucian Grainge, UMG’s Chairman and CEO, has well-known views on AI in the music industry: From early calls for UMG to commit to protecting artists against unethical uses through ‘a more equitable and more vibrant music ecosystem that rewards all artists’ (here, here and here), to Grainge welcoming 2026 by issuing a ‘stark warning about irresponsible business models in AI music’ while acknowledging the use of AI tools to aid creativity. It appears that the initial AI panic has yielded to a more tempered approach, selective licensing.

The expanding list of AI-related agreements (this Kat counts 12) confirms as such. Further, the threat of litigation remains a significant step to nudge unethical players as the UMG and Udio agreement (IPKat here) demonstrates; a process that Suno will likely follow. Responsible AI rhetoric, which reserves litigation for only truly ‘unethical players’, shapes market norms, deters investment in ‘rogue’ AI startups, and preferences label-approved licensees.

Certainly the ‘move fast, break stuff’ AI start up ethos amplifies the issue, but this level of private ordering forecloses key discussions on the doctrinal application of the copyright system to AI training and generated output. It also provides a foundation for sector-specific driven norms to become the legislative blueprint despite copyright’s horizontal application across sectors.

**Shifting focus from AI slop to an AI music stack **

These strategic partnerships signal UMG building a layered tech ecosystem where control extends over the nature of the AI models, licensed data, ownership of output and control over platforms for user engagement-related data. The press release characterises this closed ecosystem as ‘revolutionary’ for artists. In particular, the artist incubator where ‘artists, songwriters, and producers’ can ‘co-design and test new AI-powered tools, integrating them into real-world creative workflows’.

While artists may have the potential to shape the future of UMG’s ecosystem, this Kat contemplates the impact of the artist incubator on the future of the broader music sector. In 2024 it was reported that 25% of music producers use AI during the creation process while an AI company-related survey towards the end of 2025 suggested, at least for workflow, 87%. Bias aside, increasing reliance on AI during the music workflow process challenges perceptions of AI-assisted generation and its relationship to human creativity; hinting that it might already be an open secret within music production. Naturally this already a concern for the Grammys next month, with one nominee recently recounting their experience with AI-assisted production.

Even further questions loom over the future use of artist incubator-generated data. This ‘farming’ of data will likely be used to train Music Flamingo models and further entrench UMG’s market dominance over AI-assisted music production reducing competition from independents or open AI; all via licensing norms that sideline sector-neutral exceptions. This a quiet expansion of copyright’s reach through UMG’s acquisition of AI stack layers that provide scalable computer power and an increasing monopoly for music’s current frontier. One that ‘fortuitously’ positions them as the only viable option for AI-related music creativity.

**NVIDIA’s vertical move **

NVIDIA dominates the AI infrastructure market. With 67 venture capital deals last year, NVIDIA’s stock price has soared, making it a ‘$4.6 trillion market company.’ It has openly stated that it seeks to ‘fuel the AI revolution with investments in game changers and market makers’. It does so through its own AI stack that comprises core computing hardware (GPUs), high speed scalers (e.g. InfiniBand or Spectrum-X), hardware-related proprietary software for developers (CUDA), and foundational models alongside domain-specific platforms (e.g. Music Flamingo).

Music is being absorbed into this pattern. UMG’s licensed catalogues now train Music Flamingo, providing rich data which they describe as ‘groundbreaking’. As outlined above, the artist incubator-generated data will likely also be used test and refine Music Flamingo’s ‘human-like’ reasoning, creating standard metrics only UMG/NVIDIA can control. Further the music discovery optimisation means that end-users will increasingly be locked-in to this closed ecosystem (e.g. personalised playlists, mood-based searches, and artist tools). The final contractual layer gatekeeps creativity through terms and conditions, allowing access according to the AI music stack’s established norms.

Given the ‘significant data centre infrastructure’ required, NVIDIA’s business model positions them to benefit from the licensed deployment of Music Flamingo through the artist incubator and discovery tools. While press releases emphasize collaboration, NVIDIA’s** subscription-based software licensing** could result in revenue from UMG’s internal scaling. If other platforms eventually integrate Flamingo, they will also pay per-token or user for ‘human-like’ recommendations powered by UMG data. It’s possible that NVIDIA will also bundle its compute hardware and models into enterprise packages for music industry internal tools.

This a finely-tuned NVIDA strategy where the offer of data infrastructure and AI deployment tools concentrates power over other AI stack layers and drives more demand for its compute hardware and software (e.g. Scale AI and Cohere discussed here). Some reflect that the sheer number of ‘investments’ details ‘how far and wide NVIDIA have spread its tentacles into the tech industry, beyond supplying its products’.

**Comment **

Now we are witnessing these tech tentacles wrap themselves around music catalogues, artefacts of human creativity, to transform them into controlled interfaces for AI music production and beyond. With severe implications for who defines music and who gets to make music, this AI music stack should concern us. The existence of models trained outside of label-approved platforms will surely dwindle given NVIDIA’s control over compute, models and data access. It means that rules are being written over AI-assisted music production norms.

So cautiously applaud AI discovery tools and approaches that use artists as human shields to concentrate power (again). Take a peek underneath the finely-crafted rhetoric as this agreement ensures access to structured and licensed data streams for models, not just artist empowerment. It captures a layer of AI infrastructure, narrows the space for future AI-assisted music production competition, and sets copyright norms to the detriment of public-interest training rights. Anything that unlicensed AI-assisted workflows generate becomes infringing without testing the boundaries of exceptions.

As Morpheus explains to Neo:

You take the red pill…you stay in Wonderland, and I show you how deep the rabbit hole goes.

If you take the blue pill, this pre-filtered future, where ‘responsible AI’ ‘farms’ artistic data into label-protected workflows and innovation, will surely entrench power through licensing monopolies that erode artistic autonomy and choice.

Music matrix overloaded - UMG’s ‘artist incubator’, a blue pill for music-related data farming? Reviewed by Georgia Jenkins on Monday, January 19, 2026 Rating: 5