Can Musicians Survive the AI Music Boom?

AI-generated tracks are showing up on major platforms like Spotify, often under the names of independent musicians. These uploads can divert listeners and royalties, creating confusion about what is genuine. For artists who depend on streaming income, even small losses matter. The deeper concern is that people may stop noticing, or even caring, whether the music they are enjoying was made by a person at all. Once authenticity stops being a priority, the emotional and cultural value of music is at risk of eroding.

The experience of Sheffield-based folk singer Emily Portman illustrates the problem. She discovered that a full album called Orca had appeared online, released under her name but generated entirely by AI. The track titles echoed her real songs, but the performances were unnaturally flawless. Portman told TechRadar: “I'll never be able to sing that perfectly in tune. And that's not the point. I don't want to. I'm human.” For her, the issue is not only about identity theft but also about losing the imperfections that make music personal and alive.

Other musicians are dealing with similar situations, finding AI-made tracks misattributed to them. These fakes often sound eerily close to the originals but lack the emotional weight of a lived performance. Instead of capturing vulnerability and artistry, the songs feel, in Portman’s words, “vacuous and pristine.” For many, the worry is not just about stolen revenue but about being replaced by a copy that listeners cannot or will not distinguish from the real thing.

The flood of AI content on streaming platforms is already straining the system. Reports show that fake albums and cloned tracks are diluting royalties and filling catalogs with music that never passed through a studio. Each AI upload reduces the pool of earnings available for real musicians, who already struggle with razor-thin payouts. Streaming services have begun removing some AI-generated uploads, but enforcement is inconsistent, leaving artists to chase down violations themselves.

At the same time, record labels are beginning to experiment with AI as part of their business models. Platforms like Suno and Udio allow anyone to create polished tracks instantly, and some labels see these tools as a way to cut costs and pump out endless music. For companies, it’s efficient. For artists, it could mean competing with machines that never rest. This shift raises questions about whether labels will still invest in nurturing human talent or whether synthetic voices and AI-crafted personas will dominate future catalogs.

The bigger picture is about value. Music has always been more than just sound, it reflects lived experiences, cultural identity, and personal expression. If AI music becomes normalized, it risks reducing songs to mere content, stripping away the connection between the listener and the human behind the art. Emerging artists, who often bring originality and new perspectives, could be pushed aside before they have a chance to grow an audience.

AI in music is not going away, but the way it is handled will shape the industry’s future. Clear rules around attribution, royalties, and labeling of AI-made songs are needed to prevent misuse. Without protections, smaller musicians will continue to bear the heaviest burden, losing both recognition and income to systems built on their creativity. The challenge is to embrace innovation without erasing the people who give music its soul.

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