This report is part of our Season 3 research sprint on creative AI for the music industry.
Investment and hype around generative AI tools are higher than ever, and momentum around music and audio AI in particular 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 music creators and rights holders. 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.
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