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.

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.

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.

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.