Last year, I started experimenting with AI music tools out of pure curiosity. Like many musicians, I kept hearing more and more about artificial intelligence being used in music production, and I wanted to understand firsthand what these tools were actually capable of beyond the headlines and hype. I began incorporating platforms like Suno into my production workflow, not as a replacement for songwriting, but as a way to speed up the production process and explore ideas more efficiently.

At the beginning, this was simply an experiment. I wanted to see whether AI could realistically support a professional workflow or whether it would feel like a novelty that lacked emotional depth. I approached the process cautiously, testing how AI could fit into the creative process without compromising the integrity of the songwriting itself. What I discovered fairly quickly was that these tools could dramatically accelerate production while still allowing me to maintain full creative control over the music.

I’m Still Writing My Own Songs
Although I’ve experimented with prompting Suno to generate tracks, I’m still writing all of my songs the same way I always have. I’m still creating the lyrics, chord progressions, melodies, and overall direction of the music.

Personally, I find that process far more rewarding, and from my perspective as a songwriter, nothing has really changed creatively. The emotional core of the music still begins with the same spark of inspiration, and the songwriting still develops through the same instincts and musical sensibilities I’ve always relied on.

In other words, AI isn’t replacing songwriting. It’s assisting with production. The biggest difference is the speed at which I’m able to move from idea to finished track. Instead of spending days or weeks building arrangements from scratch, I can explore multiple sonic directions quickly, refine the results that best support the song, and release music more consistently. The creative process itself still feels very familiar, but the workflow has become significantly more efficient.

The Most Prolific Songwriting Period Of My Career
One unexpected result of working with AI tools is that this has become the most prolific period of my career in terms of songwriting, by a huge margin. Because production barriers are lower, I’m able to follow creative ideas more freely without getting slowed down by the technical side of building tracks from scratch. Instead of spending large amounts of time trying to fully produce one song before moving on to the next, I can capture ideas quickly while inspiration is fresh. I've had days where I've written and produced multiple songs in a single day!  

That shift has allowed me to write and produce significantly more music than I was creating before. Ideas that might previously have stayed unfinished are now becoming completed tracks. Concepts that I might not have had time to explore in the past can now be developed quickly and evaluated creatively rather than technically.

As a songwriter, that has been incredibly energizing. The faster workflow has made it easier to stay in a creative mindset and maintain momentum, which has resulted in a much larger catalog of finished music over a relatively short period of time.

From Casual Experimentation To Dozens Of Tracks
Over several months, what began as casual experimentation turned into something much more substantial. I ended up creating dozens of new tracks using AI-assisted production tools, often starting with ideas I had written traditionally and then using AI to help shape the production. Many of these songs began as creative exercises that I was doing mainly for fun in the beginning, but over time I found myself genuinely happy with many of the results.

The ability to quickly explore arrangements, instrumentation, and sonic textures opened creative possibilities that would have taken significantly longer using traditional production methods alone. Instead of getting stuck trying to perfect a single production direction, I could test multiple approaches and follow the one that felt most compelling. That freedom made the process more enjoyable and more creatively stimulating, and it allowed me to focus more energy on songwriting rather than getting slowed down by technical barriers.

As the catalog grew, I decided to move forward under the assumption that the legal and business frameworks surrounding AI-assisted production will eventually become clearer. The music industry has always adapted to new technologies, from multitrack recording to sampling to digital production.

Each shift initially created uncertainty, but standards and best practices eventually emerged. From my perspective, AI-assisted production appears to be following a similar pattern as the industry works through questions related to copyright, disclosure, and licensing.  It's still a grey area, and I have talked to music supervisors who have expressed to me they don't want anything to do with "AI Music", but some libraries are starting to openly sign "AI assisted" tracks, and I feel like more will follow suit in the future.  The technology is simply too powerful and behind the scenes, more and more musicians are embracing it.

Signing My First AI-Assisted Tracks To A Music Library
Recently, I reached an important milestone when I signed my first batch of AI-assisted tracks with one of the music libraries I already work with. This felt like a meaningful step forward, because while this particular library is the first in my network to openly accept AI-assisted tracks, I expect more libraries will begin to follow as the technology becomes more widely understood and as clear policies continue to develop.

Music libraries ultimately care about whether tracks are usable, licensable, and emotionally effective. If a piece of music supports a scene, enhances a story, or communicates a feeling clearly, it has value regardless of how it was produced.

As long as the underlying songwriting is solid and the rights are clearly defined, AI-assisted production is increasingly being viewed as another tool available to composers. 

This moment reminds me of earlier transitions in music technology, where initial skepticism gradually gave way to acceptance as the benefits became clearer and the workflows became more refined. Technologies that initially seemed controversial eventually became standard parts of professional music production.

AI Music Is Becoming More Legitimate
We’re already seeing signs that AI music is becoming more widely accepted within the broader music ecosystem. My alma mater, Berklee College of Music, is now offering coursework that explores how AI tools can be used in songwriting and production workflows.

In response to criticism surrounding one of its AI songwriting courses, Berklee stated:

“As an artist-first institution at the forefront of contemporary music and performing arts education, Berklee has a responsibility to prepare our students to navigate technologies impacting the creative industries. We will continue to do so, in keeping with our guiding principles.”

This reflects a broader shift taking place across the industry. Educational institutions are recognizing that AI is becoming part of the modern creative landscape, and rather than ignoring the technology, they’re choosing to educate students about how it works and how it can be used responsibly. As AI tools continue to improve, more musicians, producers, and educators are exploring how these technologies can coexist with traditional musicianship rather than replace it.

Read the rest of the article and hear examples of some of the AI assisted tracks I've signed to music libraries, here.

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