AI-Generated Music: Creative Revolution or Cultural Devaluation?

AI has already proven itself in fields as diverse as medicine, logistics, and coding — but in recent years, it’s made its way into a much more emotionally charged arena: music.

From AI-generated tracks in the style of Drake and The Weeknd to surreal mashups by parody creators like thereiruinedit, the landscape is shifting fast. Artists like Grimes are not only embracing AI’s role in music production — they’re actively inviting others to create AI-generated tracks using her voice, offering a royalty split to those who do.

The rise of AI in music brings up urgent questions: Is this a tool for empowerment or imitation? Does it democratise creativity, or dilute it? Does it devalue art — or make human expression more valuable than ever?

In my opinion, it’s not a binary issue. Like the introduction of synthesisers, sampling, or digital audio workstations before it, AI is another evolution in how music is made. But it also brings a new kind of existential challenge.

The Artists Embracing AI

Some artists see AI not as a threat, but as an invitation to play with the very boundaries of what “music” is.

Grimes, for example, has openly declared that she’ll split royalties with anyone who creates successful music using her AI voice model. For her, AI isn’t stealing — it’s scaling. It’s an opportunity for her creative identity to extend beyond her own limitations and into an open-source ecosystem of fans and collaborators.

Then there are creators like thereiruinedit, whose AI-assisted parody mashups (“Johnny Cash covers Barbie Girl,” “Kanye sings Bohemian Rhapsody,” etc.) are bizarre, hilarious, and oddly insightful. They use AI not to replicate sincerity but to amplify absurdity — creating a new kind of musical commentary that wouldn’t be possible without synthetic tools.

From what I’ve seen, the artists who thrive in this space are the ones who treat AI not as competition, but as a new instrument in the studio.

The Pros: Accessibility, Speed, and Infinite Experimentation

There are undeniable benefits to using AI in music creation:

Lower barriers to entry: Anyone with a laptop can generate melodies, harmonies, beats, or lyrics. You don’t need a full band or years of formal training to begin creating music.
Rapid iteration: AI tools can generate dozens of variations on a theme, helping artists experiment quickly and refine ideas faster.
Collaboration at scale: With voice models and generative instruments, artists can blend styles, cultures, and sounds in ways that were once impossible or impractical.
New genres and art forms: We’re seeing the birth of entire subgenres — AI remixes, surreal parodies, and fully synthetic artists like FN Meka — that wouldn’t exist without this technology.

Much like the introduction of synthesisers in the 1970s and 80s, AI opens up entirely new sonic possibilities. It’s worth noting that the legendary rock band Queen initially included a proud statement on their early albums: “No synthesisers.” Yet by the time of The Game (1980), they had embraced electronics fully — not out of necessity, but out of a desire to evolve creatively.

The same arc may repeat here with AI.

The Cons: Authenticity, Over-Saturation, and Ethical Grey Areas

But the excitement comes with caveats — and not small ones.

Authenticity is harder to verify: As AI-generated content becomes more convincing, it becomes increasingly difficult to tell what’s real and what’s synthetic. This blurring could lead to a crisis of trust in music, where audiences no longer know who — or what — they’re listening to.
Devaluation of originality: If thousands of AI-generated songs can be pumped out in seconds, does that flood the market and make human-crafted work harder to find or appreciate?
Voice and identity cloning: The ability to replicate an artist’s voice without consent raises serious legal and ethical concerns. Some AI covers may be amusing or flattering; others may be harmful, misleading, or outright malicious.
Cultural erasure: When algorithms are trained on massive datasets, they often strip away context and meaning. There’s a risk of homogenising the very cultural diversity that gives music its soul.

From my perspective, the concern isn’t just about replacing musicians — it’s about overwhelming listeners with content that feels hollow, derivative, or artificially sentimental.

Does AI Devalue Art — Or Reignite Its Importance?

There’s an argument to be made — and I find it increasingly compelling — that AI-generated content may actually increase the value of human-made music.

Just as handmade goods become more sought after in an age of mass production, listeners may begin to seek out music with verifiable human origin. Live recordings, behind-the-scenes footage, songwriting breakdowns — these become badges of authenticity in a world flooded with synthetic sound.

Rather than destroying artistry, AI may shift the focus. From “can I make music?” to “why did I make this?” From novelty to narrative.

In that sense, the cultural shift might not be about AI taking over music — but about redefining what we value in it.

A New Instrument, Not a Replacement

AI is neither the death of music nor its saviour. It’s a tool — powerful, strange, and full of both risk and promise.

Like the electric guitar, the drum machine, or the autotuner before it, AI is reshaping music in ways that challenge our assumptions. And like Queen with synthesisers, every artist will need to decide where — and how — they draw the line.

In my opinion, the best outcomes will come from collaboration, not confrontation — from musicians who understand AI, and AI that understands music.