The state of music AI tools
This report is part of our Season 3 research sprint on creative AI for the music industry.
The hype around music and audio AI models is gaining more steam. Already in 2023, over 10 different music AI models have been released by independent researchers and big-tech companies like Google and ByteDance, allowing users to generate custom tracks in seconds using a mere text prompt. Hundreds of thousands of AI-generated songs are now listed on streaming services, raising concerns around content oversaturation, attribution, and monetization for the music industry at large.
And yet, little to no writing or market analysis has distilled the music AI landscape in a way that understands the unique behaviors, product needs, and business models of existing creators and rights holders in the music industry. That’s where we come in!
Over the last few months, several researchers in our community came together to build a comprehensive, first-of-its-kind framework for understanding music AI tools landscape — including greater transparency into tech stacks, use cases, and business models for all stakeholders in the music AI value chain.
We conducted this research primarily with the following industry stakeholders in mind, as business decisions around music AI most directly impact them:
- Startup founders looking to understand current practices for building and growing music AI companies.
- Investorslooking to identify trends and under-explored opportunities in the music AI market.
- Creative professionals looking to incorporate music AI tools into workflows.
- Music rights holders looking to build commercially defensible tech strategies and partnerships as music AI tools become mainstream.
We employed a multidisciplinary methodology, including:
- Curated database of music AI tools. In collaboration with our community members, we assembled a living database and market map of over 80 music AI tools across the creative lifecycle, from lyric writing and chord generation to mixing, mastering, and audio synthesis.
- Qualitative interviews with music AI startup founders . To supplement our database, we interviewed over a dozen founders to understand the key opportunities and challenges in building music AI startups today. You’ll see quotes from these interviews scattered throughout the report.
- Calls and resource-sharing in the Water & Music Discord server . To develop a collaborative learning culture, we held weekly project discussion calls in our Discord server, chatting through findings from our interviews and exchanging notes and resources asynchronously on the evolution of the music AI landscape. Many of our community members are building and exploring these tools in real-time, giving our research a critical, practical grounding.
You can view the full report below (recommended to view on desktop), and catch up on the rest of our creative AI research on our STREAM landing page . Thank you so much for your support!