AI in Music: Imitation vs. Empowerment
Like so many of the rapidly changing circumstances today, AI in music is a polarizing and game changing technology that is here to stay whether you accept it or not. SAW wanted to look at this from as many perspectives as possible. At SAW we have been playing with AI’s uses in music and watching the reactions it generates for a while, so we thought it time to communicate.
It’s obvious that artificial intelligence is rapidly reshaping the music industry, but not all uses of AI tools are equal. Broadly speaking, there are two very different paths emerging.
One treats AI as a replacement for human creativity—generating songs that mimic what already exists.
The other uses AI as a production tool—augmenting human artists, lowering barriers, and accelerating the creative process.
Both very different types of AI have met with an instinctive disapproval that is understandable. It does lose sight of the possible positives. That same intense disapproval happened in the last century when records (1920's), electric instruments, midi/synthesizers, home DAWs, Autotune and other tools came along to shape live and recorded music. In each period these innovations were decried as "the death of music". But real artists did and will adapt, adopt and explore the uses of new technologies because creativity always finds a way.
It is important to separate these two distinct uses of AI in music for human beings. They may appear similar to the fearful untrained eye. But using AI to generate approximations of original songs/music based on massive sampling and modeling of other songs is oceans away from using AI to speed, democratize and make affordable the production process for songwriters and musicians by augmenting human artists, lowering barriers, and accelerating the creative process.
Understanding this distinction is critical, because these two approaches don’t just differ technically—they reflect opposing philosophies about what music is and who it’s for.
1. AI as a Generator of “Human-Like” Music
One of the most visible uses of AI in music today is generative composition: systems trained on massive datasets of existing songs that can produce new tracks in similar styles. These models analyze patterns—melodies, chord progressions, rhythms, vocal tones—and recombine them into something that sounds familiar, even convincing.
At first glance, this feels impressive. You can prompt an AI to create “a beatles-style song” or “a 90s grunge track,” and within seconds, you get a polished output. But under the hood, this process is fundamentally derivative.
AI-generated music of this type is:
- A statistical remix of existing works
- Built on pattern recognition, not lived experience
- Optimized for plausibility, not originality
It doesn’t intend anything. It doesn’t struggle, experiment, or break rules. It simply predicts what should come next based on what it has ingested as data before.
Songs and music have always been more than structure—its expression shaped by:
- Emotion
- Context
- Culture
- Imperfection
When AI generates a song purely from data, it lacks those grounding forces. The result can sound “right,” but often feels hollow on repeated listening. It’s convincing, but rarely compelling.
It is predicted this approach will eventually:
- Flood the market with generic, interchangeable music
- Devalue human artistry
- Shift focus from meaning to mere consumption
In short, it treats music as a product to be manufactured, rather than a medium of expression. While that may appeal to business and those who seek fame over authenticity but most of us will tire of that product and it will lose its grip on the industry over time and may harm music creation in ways we can only speculate about.
2. AI as a Production Tool and Creative Multiplier
Now contrast that with a different use of AI—one that doesn’t try to replace the artist it empowers them.
Here, AI is not the creator. It’s the assistant.
What This Looks Like in Practice
- AI tools are already helping musicians:
- Clean up recordings (noise removal, vocal tuning)
- Generate rough drafts or idea starters
- Suggest chord progressions or harmonies
- Automate mixing and mastering
- Convert hummed melodies into full arrangements
These tools don’t decide what to create—they help artists execute their vision faster and more effectively.
The Real Impact
This approach fundamentally changes access to music production.
What once required:
- Expensive studio time
- Specialized engineers
- Years of technical training
Can now be done:
- From a laptop
- At a fraction of the cost
- By independent creators anywhere in the world
Why This Matters
This is where AI becomes transformative in a positive way:
- It democratizes music creation
- It reduces financial barriers
- It allows artists to focus on creativity instead of technical friction
Instead of replacing musicians, it expands who gets to be one.
3. The Sharp Contrast
At a glance, both uses involve AI and music. But their implications couldn’t be more different.
| AI as Generator |
AI as Tool |
| Replaces human input |
Enhances human creativity |
| Derives from past data |
Enables new expression |
| Focuses on output |
Focuses on process |
| Risks homogenization |
Encourages diversity |
| Lowers effort, no insight |
Lowers barriers, not meaning |
One approach asks: “Can AI make music instead of us?”
The other asks: “How can AI help make and produce my music?”
That difference is everything.
4. Where This Is Headed
The future of music will likely include both paths—but they won’t be valued equally.
AI-generated songs may dominate low-stakes environments: background music, content filler, algorithm-driven platforms.
Human-driven music, supported by AI tools, will continue to define what resonates deeply with people.
Because ultimately, listeners don’t just respond to sound—they respond to intention. And artistry is mindful of the past but not shackled by it as imitation always is.
AI can imitate music, but it doesn’t care about it. Artists do.
The most meaningful use of AI in music isn’t to replace that human element—it’s to remove the obstacles around it. When used as a tool, AI doesn’t diminish creativity. It gives more people the chance to express it.
Love it, hate it or just don’t care, AI is going to change the landscape of music creation and production. Learning about it will not make you weak but leaning on it in a lazy fashion will do just that. The future belongs to those who can adapt and remain in control of their vision, creativity and expression.
Thanks,
Jay Keating and Kelly Diamond
SAW Leadership Team
