AI Music vs Underground Musicians: The Fight to Still Matter As An Artist
Before I dive into one of the many topics that have been at the forefront of my mind and those of many others I work alongside, I want to take a moment to express my genuine appreciation for everyone reading, as well as the platforms that continue to allow me to have a voice. I’m grateful not only for the chance to explore subjects I believe are important and publish thoughtful breakdowns, but also to be trusted to help bring these conversations to the forefront.
Over the rest of September, I'll cover what I've learned and speculated on about the use of AI and AI tools circulating throughout the underground music industry. With the number of tools, information, and ways to use AI increasing daily, there's a lot to cover. Therefore, I will need to piece this up into a few sections to break down my full perspective on the topic: AI-generated music, AI audio tools and how we use them, and lastly, I would like to theorize on different outcomes of where we may be headed as humanity as we move forward with this frighteningly unstoppable force in technology.
If you’d like a quick synopsis on AI music and how it's now battling among real talent for the same audience, you can find it in the Heartbreak Newsletter, published by Heartbreak Records in Boston, Massachusetts. More than anything, the goal isn’t to share my point of view, but to open the floor to conversations that concern many of us in the underground music scene. I welcome any feedback, rebuttals, and suggestions for new topics worth digging into.
Welcome To The Automated Age
Over the last few years, Artificial Intelligence has become impossible to ignore. Since it first became accessible for public use in 2022, AI has entered every corner of the creative world. In music, we now have AI-assisted production, automated mastering, synthetic vocals, generated beats, and systems capable of creating complete songs from a few written instructions. But I think the usual question that people ask is, “Will AI replace musicians?” misses the bigger issue. A better question is: What happens when creating music becomes so easy that there is practically an unlimited supply of it?
What Do I Mean by "AI Music"?
First, let's get on the same page when I mention the terms "AI Music” and “AI Tools”, because after looking at all the software that is used to mix, clip, master, or even experiment with their sound, AI can do more than manufacture tunes. When people think about AI-generated music, the ultimate goal is often a program that can create completely original songs from scratch. The result gives anybody the ability to generate lyrics, instrumental, arrangement, and singing voice for an entire song with relatively little human involvement. To give you a better idea of what I mean, your 10-year-old brother can type a sentence into a computer and receive a finished original song a few seconds later. While we’re not at the point where AI can combine the genius of Mozart with the creativity of The Beatles, that seems to be the direction where this technology is moving.
AI music works through a process known as deep learning. In simple terms, an AI system is trained using massive collections of music so it can learn how different songs are put together, from their rhythms and melodies to their styles and overall structure. Once it picks up on these patterns, the AI can use what it has learned to create music based on a text prompt or description provided by the user. Two popular examples of this technology are Suno and Udio, which allow users to turn simple written prompts into original songs with vocals, lyrics, and instrumentals.
As for the term “AI tools,” it refers to the new advances in our recording and mixing software, utilizing AI to streamline your musical productivity as an artist or producer. Nowadays, AI can be involved at almost every stage of making music. A producer might use it to separate vocals and instruments from an existing recording, clean up audio, help master a song, experiment with arrangements, generate musical ideas, or create a temporary vocal while developing a track.
The difference between the two ways it's being used matters because using AI as a production tool is not the same as replacing the creative process entirely. A musician using AI to clean up a recording is very different from someone automatically generating thousands of finished songs. Creating an original artificial voice is also different from deliberately making a voice sound like a recognizable artist. These uses raise different creative, cultural, ethical, and legal questions. As AI becomes more common, audiences will need a better understanding of how it is used so people can discern for themselves if involving AI is a good or bad addition.
AI Music and Short-Form Content (An Unfavorable Duo)
One place where AI music makes immediate sense is short-form video and advertisements. TikTok, Instagram Reels, YouTube Shorts, and similar platforms have created a constant demand for new audio. Big creators aren't necessarily producing one polished commercial or music video every few months. They are uploading several videos a day. That creates a need for background music, transition sounds, theme songs, short hooks, comedy songs, promotional jingles, and other forms of audio.
Traditionally, a creator might search through a music library or choose whatever trending song happens to be popular. AI introduces another possibility: instead of finding music that is close to what you need, you can now generate a song and clip it specifically for the video.
FLOOD WARNING: AI Slop Is Filling Our Feeds!
There is another problem that I believe will get much worse over time: the volume of content that gets posted. AI does not simply make music easier to create; it makes music incredibly easy to mass-produce. The numbers are already significant.
In January 2025, the streaming service Deezer reported receiving roughly 10,000 fully AI-generated tracks per day, representing about 10% of its daily music deliveries. By November, that number rose to nearly 50,000 each day. This year, in June 2026, Deezer said it was receiving as many as 90,000 fully AI-generated tracks per day, exceeding half of the new music delivered to the platform at peak before AI music was around. That does not mean half of what people are actually listening to is all generated. Fully AI-generated music still represents only a small percentage of streams, but the upload numbers are dominating the statistics. Think about what that means for an underground artist. A human musician might spend weeks writing, recording, mixing, mastering, creating artwork, shooting videos, and planning a release. During that same period, generative systems can produce enormous quantities of songs and promotional content.
Social media adds another layer to this issue because that is where it’s primarily consumed. Artists are already competing inside feeds overflowing with songs, videos, images, memes, influencers, advertisements, and other entertainment. AI gives everyone the ability to create even more, maybe too much. This tsunami of content will undoubtedly create a public fatigue of AI music being used virtually everywhere. Think of an endless supply of content overwhelming our feeds that may be impressive but nothing to remember or even care about. To put this in a way that you can visualize. Catchy tunes like the iconic O'Reilly Auto Parts jingle, or the comical 411PIAN radio tunes (which I still sing to this day) will become things of the past. Jingles, episode transitions, and end credits will be built for attention rather than a musical memory that can stick in the minds of a generation.
The Opportunity Depression Is On The Way
This is where my biggest concern is for artists and producers alike. When people talk about AI replacing musicians, the conversation often jumps immediately to superstars. Can AI replace generational talents like Beyoncé, Drake, Taylor Swift, or other major artists? That probably is not where the first major issue is being seen so far. Producers, beatmakers, jingle writers, session musicians, background vocalists, stock-music composers, and people creating music for podcasts, advertisements, YouTube channels, and social-media campaigns may be much more exposed. Those jobs might not generate headlines, but they matter. I mention these intricate professions because these are some of the most common gigs for musicians to live off of their craft.
A producer earning $500 for a small advertising project might use that money to pay bills while developing an album. A session musician might make a connection that leads to a larger opportunity. A composer creating inexpensive background music can build a portfolio that eventually leads to television, gaming, film, or larger advertising work. So when AI “saves” a company $500, we should also ask where that $500 used to go. For an outlet like our team at SpinBinMag, who are dedicated to discovering independent talent, that question also matters to us. The musicians most vulnerable to losing smaller creative opportunities are often the same people independent music media support. Therefore, the outcome for underground musicians and independent artists will be similar to where this platform roams.
Discovery Is Now A Bigger Battle
For years, an important question for an underground musician was, “Can you make music good enough to draw attention?” That question still matters, but another one is becoming equally important: “Can you make people care that you were the person who made it?”
This is where we must rethink what promoting music actually means. Posting a cover image and a streaming link to your story or a small snippet release may not be enough anymore. The story behind YOU as the artist becomes much more important. Interviews become more important. Live footage becomes more important. Behind-the-scenes material becomes more important. Showing audiences the person behind the song becomes more important. Strangely enough, the growth of AI music may make human-made music more valuable in the long run. Although AI will cause a handful of complications for artists today, I have faith in our need for authenticity as a society.
When we ultimately end up in an environment filled with this manufactured perfection, those imperfections might start feeling less like flaws and more like proof that something is human. After the fog of confusion fades, people may lean even harder into the things that prove there are actual people behind the culture. Live performances, backstage conversations, artist interviews, local events, studio visits, creator stories, and footage showing how something was made could become more valuable than ever before. If content becomes cheap to make and simple to generate, access to real people and real experiences becomes priceless.
Where Does That Leave Us?
I hate to say it, but I don't think AI music is going away, and trying to stop every possible use of it isn't realistic. That cat is unfortunately out of the bag and has been for too long. For independent artists, the bigger question is “how to use these tools without losing what makes an artist worth paying attention to in the first place?”
AI can give us access to tools that once required a bigger budget, larger team, or a professional studio. It can help with production, visuals, promotion, and repetitive tasks, giving artists more time to make music, perform, connect with fans, and develop their craft. But the same technology that gives independent artists more power gives everyone else more power too. Artists aren't just competing against other musicians anymore. They're competing for attention in a world increasingly flooded with both human and AI-generated content.
In an oversaturated market, having a polished track won't be enough. Being memorable matters more than ever.
An independent artist's biggest advantage may be the things AI has the hardest time manufacturing: identity, perspective, lived experience, relationships, reputation, and community. Play the small show. Talk to the people who came. Show how the song was made and explain why you wrote it. Let people see the rehearsals, mistakes, unfinished versions, late nights, and everything that makes the music yours.
AI can generate another song, beat, image, video, caption, or voice. What it can't automatically generate is a reason for somebody to care about you. For independent artists and creators, that may become the most valuable thing of all.
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