Creative AI may be the most disruptive technology for the music business since the Napster era of piracy. 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. At large, generative AI tools for audio, text, and visual art have picked up tens of millions of users, forcing us to rethink traditional notions of creativity, ownership, and attribution.

At this critical juncture, we’re thrilled to release our Season 3 report on creative AI, which provides a comprehensive guide on the technology’s emerging opportunities and challenges for music. Over the last three months, more than 50 contributors in our community came together to analyze and discuss the impact of creative AI across the music-industry life cycle, from music creation and ideation to distribution and monetization. We curated a database of over 40 different tools, annotated the terms of service for 11 AI companies, interviewed 15 different artists and startup founders, and ran an AI ethics and sentiment survey with over 150 responses.

Our goal with this report is to bring more transparency on the current state of music AI to anyone with a stake in the outcome, including artists, rights holders, software developers, and startup founders. We hope our findings provide a helpful starting point for understanding the critical commercial, legal, and ethical issues at stake as AI continues to transform the business of creativity at large.

Join the Water & Music membership today to access the full report, and stay up-to-date on emerging tech developments with our community of music/tech creators, leaders, and innovators:

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The state of music AI tools

Digging into music AI tooling, use cases, and business strategies across the creative lifecycle.


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AI sentiment across the industry

Understanding music-industry needs and sentiments around creative AI, from a survey of over 150 stakeholders.


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AI and music copyright

Addressing artists' legal questions about creative AI and ownership, through the lens of AI tools' terms of use.


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Building a creative AI community

Looking behind the scenes at how we built a community around creative AI experimentation.


The state of music AI tools

This section covers all things business strategy for music AI, understanding how music AI companies address their users' needs and build out their business models in an increasingly competitive market.

Navigate the music AI landscape — We spoke with over a dozen music AI startup founders and assembled a living database of over 80 music AI tools across the creative lifecycle to build a framework mapping both high-level market opportunities and on-the-ground operational challenges.

Differentiate your brand and user experience — We identified specific leverage points for entrepreneurs to build more targeted and delightful AI experiences across particular user segments and for artists and rights holders to establish their sonic footprints in an AI-forward creative landscape.

Understand pricing and deal structures — We compared approaches to training data, tech stacks, and pricing models across several music AI use cases to help stakeholders identify which approaches work best for specific target markets.

Temp check: AI sentiment across the music industry

This section presents our findings on music-industry needs and sentiments around AI from a survey of over 150 industry stakeholders, including artists, industry professionals, and tech builders.

Design better music AI workflows — We asked survey respondents to identify how they currently use and hope to employ creative AI tools in their workflows and practices and what excites them about the future of creative AI at large. Their responses will help builders better design products that meet artist and end-user needs. They will also give artists new ideas for implementing AI approaches in their creative and business practices.

Understand major stakeholder concerns around creative AI — We asked survey respondents to speak to their primary fears regarding creative AI tools. Their responses highlight important areas of concern that all those building in the ecosystem should be aware of and develop clear stances on, including but not limited to anxiety over supply- and demand-side market disruption, legal ambiguities, and bias in AI models.

AI and music copyright: A field guide for artists and developers

If you have legal questions and concerns around creative AI, this section is for you. We reviewed the Terms of Service and FAQ sections for a diverse group of 11 creative AI tools, ranging from the most well-known image generation tools with millions of users to emergent music AI startups.

Understand the current state of the law regarding creative AI — We compiled a high-level primer on the latest national-level policy developments when it comes to recognizing works made with AI, including differences between training data and generated works, as well as contrasting stances across international jurisdictions.

Know the critical legal questions to ask before using a new creative AI tool — We broke out three critical questions that artists and their teams using AI tools should ask with respect to copyright ownership and exploitation. Depending on the tools and use cases, rights and protections will vary.

Building a creative AI community: Extended interview

Assembling this report was a gargantuan effort combining crowdsourced research, hands-on community management, and custom tech development. In this special conversation, Water & Music founder Cherie Hu and tech lead Alex Flores chat through how we designed our Season 3 research sprint from the ground up, and what the experience taught us about the future of music AI and the role of AI in organizational strategy at large.

Go behind the scenes in building a creative AI community — Cherie outlines our unique approach to curating creative AI workshops and demos, while Alexander walks through the philosophy behind several custom Discord bots he built for this sprint, including integrating AI models like GPT-3 and Stable Diffusion directly into our server.

Get a sneak peek at the role of AI in Water & Music’s research process — Cherie and Alex discuss how generative AI potentially touches every aspect of W&M’s research operations, from idea brainstorming to editing and information synthesis.


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Our Season 3 workshop series featured leading teams pioneering the latest advancements in generative AI-powered music production and artist tooling. They shared their expertise on training models and using off-the-shelf tools for audio and video generation, and even provided beta testing for unreleased creative tools featuring AI-powered capabilities such as timbre transfer. You can watch videos of these workshops here:



Our full Season 3 report is open only to paying Water & Music members. We're an independent, 100% bootstrapped research community — so if you find our research valuable, we'd really appreciate your support!

We have multiple support options depending on your payment preferences and budget. All financial contributors to Season 3 will be credited on this landing page.


Join our membership to get access to our Season 3 report, a private network of like-minded music-industry innovators, an archive of 200+ articles on music and tech trends, and much more — all for a fraction of the cost of traditional market research. You can join our standard fiat membership, or mint our limited run of membership NFTs to show your support for Season 3 on-chain.


Kalam Ali
Karen Allen
Gabe Appleton
Chase Baker
Katherine Bassett
Ana Carolina
CJ Carr (dadabots)
Brodie Conley
Ibrahim Conteh
Natalie Crue
Kaitlyn Davies
Gareth Deakin
Chris Deaner
Mat Dryhurst
Mike Evans
Zach Evans
Alexander Flores
Diana Gremore
Raul Guerrero
Thomas Haferlach
Cherie Hu
Dick Huey
Kristin Juel
Rania Kim (Portrait XO)
Julie Kwak
Brandon Landowski
Sarah LaReau
Jonathan Larr
Lindsey Lonadier
Yotam Mann
Marcus Martinez
Chris McGarry
Kiru Mehari
Alex Mitchell
Reuben Nathaniel
Jeff Nicholas
Moises Sanabria
Danny Scheiner
Lucas Shamanic
Manansh Shukla
Drew Silverstein
Yung Spielburg
Ivan Todorov
Maarten Walraven
Maceo Whatley
Paul Zgordan
Adam Ziff