What does Suno AI mean for music producers and the music industry?

“We all want to make technology more accessible, but we won’t get there by powering our product on the work of writers who have yet to even be acknowledged”

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Suno AI

Sharooz is an electronic music producer, studio owner and entrepreneur. He’s also known as Principleasure and is the founder of Wavetick.

Whether a producer or songwriter, it’s impossible not to feel some emotion around the hyped generative music startup Suno. Especially in light of its recent $125 million funding — the biggest music tech equity investment in over three years.

How we create music and the potential to earn revenue from our skills may be about to change forever.

If you haven’t already played with it, Suno is fun and powerful. Like a ChatGPT for music, it creates unique songs based on a simple text prompt – and does so with impressive, albeit generic, accuracy. Vocals sound realistic, even guitar solos and string sections are spliced together with a nuance rarely seen before in generative AI music. In just a few years, AI has advanced from dodgy, artifact-riddled soundalikes to a personalised jukebox capable of spitting out songs that could probably sit unnoticed in the Billboard Top 100.

READ MORE: Learn how to create custom voice and instrument audio stems with AI

The potential to damage virtually every aspect of the music industry is obvious. While virtuosic composers and experimental curators of their craft may have little to worry about, Suno could conceivably chisel away at the stock music industry, sound designers, foley creators, lyricists and the work of songwriters in virtually every genre. This could be particularly true for those who practice more traditional arrangements and chord structures, like those commonly seen in charting pop songs.

I’d like to think that organic human emotion and the poetry of heartfelt lyricism will transcend anything a machine can offer. But it’s not inconceivable that, in the space of a few years, AI output may be indistinguishable from human endeavour, especially to the untrained ear. After all, Suno is a mere glimpse at what may be possible in the near future.

Suno’s public message offers utopian promises of “moving the bar” of music creation. It’s clear the Massachusetts-based company has plans to disrupt, with the online discourse opining that the wider mission is to fully remove the barrier between music creation and casual listening — imagine personalised playlists made up of fully unique AI-generated songs, fuelled by user prompts.

If these services are creating a future where the music creator and listener become one, this gives real potential to disrupt DSPs, labels, aggregators and everything in between. At the time of writing, Suno recently announced it plans to pay the platform’s most popular “creators” $1 million in “prize money” during June 2024.

To grasp Suno’s impact, one needs to understand how their output has become so much more polished than anything else that’s come before. AI is traditionally fed on real recorded music — human-created intellectual property (IP) with complex copyright restrictions. In theory, the more ‘data’ the network can train on, the more realistic the resulting output can sound.

Nobody is quite sure of the data Suno is trained on, but keen listeners have already identified scrambled elements of distinguishable works in their creations.

Public details on training data are scant, with many suggesting there could be lawsuits from major publishers and labels in the offing. Sony Music recently sent 700 letters to leading generative AI firms warning them not to infringe their copyrights. But if the current landscape of the music industry has taught us anything, it’s that there’s no guarantee disruptive technologies will favour human creator rights or livelihoods.

The dominance of digital streaming platforms (DSPs) has only diluted existing songwriter and performer revenue further. There’s an ongoing conversation on the unfair economics of streaming, with commercial law slow to catch up on AI’s impact on existing copyrights and publishing rights.

It’s not inconceivable labels may soon license our recordings and songs into Suno by the truckload. When those deals are done, they may net you less than any DSP currently does: fractions of cents. Will the majority of subscription revenue Suno generates line the pockets of its investors and the major labels that could one day own a share in it, if or when it goes public? After all, the investors in it will be keenly expecting a return, such is the nature of venture capitalism.

To create this technology is an awesome feat. Suno sounds remarkable. It’s fun, powerful and easy to use. To embark on this journey by going a step further, disclosing training sources and collecting metrics, directly compensating dataset contributors would be a welcome play…But I don’t suppose that pays investors well.

We all want to make technology more accessible, but we won’t get there by powering our product on the work of writers who have yet to even be acknowledged, let alone compensated. Creators may be in real danger of being squeezed out of operating altogether.

Brand trust begins with responsible practice. High-profile artists will likely boycott and vilify Suno — we saw something similar with the SAG/AFTRA strikes in 2023. Suno’s millions could aid its legal challenges but could set an uneasy precedent — steal now, seek permission later [producer BT told MusicTech a similar anecdote].

Will future legislation render AI music services a gimmick unfit for public broadcast or distribution?

User terms for most generative AI services are also unacceptably vague. We see “Use at your own risk” through to “your creation is uniquely your copyright”, with little comfort for pro/broadcast use or publishing to a DSP. Licensing a bona fide, human-created sample or track may be far more beneficial than hours spent prompting an AI-generated output that’s legally unfit for purpose.

Is there an exaggeration of AI’s impact on the music industry? If Suno are to be believed, we may evolve into an entirely new class of creators, further democratising music making. After all, why settle for spoon-fed major label playlists when you can just roll your own bespoke experience? But the real threat to professional creator livelihoods seems a long way off.

The winners in this space will likely be the well-researched, steady adopters who subtly integrate AI-assisted features to aid their existing creative processes. They’ll meaningfully democratise access for tomorrow’s creators without stealing from humans, whose work has been an endeavour of learned skill, political upheaval, emotional intelligence and the very meaning of what it is to be human. They’ll translate their authentic experiences through music.

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