AI-Generated Music Market Trends

The point about "music in the style of the last decade's hits" particularly caught my eye from a revenue-focused angle in this article. The old ways of artist royalties, licensing fees, and even the marketing strategies to make a 'hit' are all put to the test when AI can generate something nearly identical in style and substance but without a 'human' touch. For years, marketers have been trying to decode what makes a hit song, a viral campaign, or a must-see movie. The algorithms could theoretically cut that chase short. We could see a deluge of 'perfectly algorithmic' hits that capture the essence of a decade's musical trends. Would this market saturation lead to higher revenues because of more content, or would it devalue the 'original' songs and saturate the market to the point where each 'hit' becomes a drop in an ocean of content? The differentiation between 'true' artistry and algorithmic imitation becomes a financial question too. We’re on the brink of technology's capabilities intersecting with human art in a way that could both amplify and diminish traditional revenue streams in the creative sectors. This article really gets to the heart of it. I love how they talk about Taylor Swift. For instance, if an AI creates a hit song "in the style of Taylor Swift," who profits? The developer of the AI? The end-user who requested it? Taylor Swift? And how do these economic considerations alter the cultural value we place on human-created art? To the question "Is AI a tool or does it steal?" As pointed out in the latest LinkedIn News, I think AI could be viewed as an extension of a human's creative process, just as a paintbrush or a musical instrument is a tool used to express creativity. In that sense, it is not "stealing," but enabling humans to reach new heights of creativity. AI as a Thief: On the flip side, AI could potentially mimic an artist's style so closely that it becomes difficult to distinguish between the original artist's work and the AI-generated work, thereby "stealing" the unique aspects that make the artist's work valuable. What's your take here? Can and should the creative industry establish a revenue-sharing model that not only accommodates but fairly compensates human artists when their 'style' becomes a template for AI-generated works? https://lnkd.in/dCYAZC_x #ai #data #revenue

Last week, I scrolled past the below post on X, so I started looking into the mysterious "Waylen Castillo," an artist with no online footprint who claims to have released an album featuring not only John Prine but also Nekxum and Pablo Mas. As Brandon Hardin speculated, Castillo possibly used AI to generate the songs, in addition to tagging artists who don't actually appear on the release. I sent this to Geraldo Ramos of Moises who ran the first track through his company's synthetic voice detection software. It found, with a ~90% accuracy rate, that the song was likely "artificial," yet the album appeared on Spotify, YouTube Music and Amazon Music. The album was pushed to people in customized Spotify playlists, and Castillo accumulated ~20K monthly listeners on the platform. I reached out for comment. YouTube and Spotify pointed me to policies preventing misleading content. Amazon didn't respond. All three platforms have since removed the album. All of which is to say, AI-generated music is likely already making the rounds on streaming platforms. General policies on synthetic voices aren't clear, but tagging real artists obviously violates terms of use. I covered this tactic, which lets unknown uploaders benefit from recognizable artists' fan bases, in May, and it remains a problem! (Screenshot from that article also below.) Are the streaming platforms ready for the onslaught of AI-generated music? Curious what y'all think below. I also wrote about this and more in my weekly newsletter about the world of audio. You can read it and sign up here: https://lnkd.in/eV6fcg58

The music industry might collapse and it won’t be because of bad songs. It’ll be because of too many songs. AI-generated content is scaling at an exponential rate. Over the next 12–24 months, the number of tracks flooding platforms like Spotify and Apple Music will skyrocket not by thousands, but by tens of millions per day. We’ve already seen the early warning signs: 🛌 “Sleeping music” literally white noise racks up hundreds of millions of streams and earns creators passive income. It’s cheaper, faster, and more efficient to create than actual songs. Now scale that concept across every genre. Every vibe. Every artist simulation. This isn’t a creative revolution. It’s a supply chain crisis. Artists will struggle to exist in the algorithm at all, and it will be a perfect storm - 1. Oversaturation of Content Millions of tracks daily = discovery fatigue. Most music won’t get heard, let alone monetized. Streaming economics implode further—fractional pennies go toward a sea of noise. 2. Devaluation of Music as Art Music becomes infinite and instantly replicable → loses perceived value. Supply outpaces demand by orders of magnitude. Like stock photos or generic AI art, music risks becoming background filler. 3. Listener Fatigue + Algorithmic Decay Recommendation engines (Spotify, TikTok) get clogged. AI content floods every niche—harder for humans to rise. Trust in discovery systems erodes. 4. Collapse of Middle-Class Creators Top-tier artists may survive due to brand/community. Bottom-tier may use AI to flood market. Mid-tier artists struggle most—algorithms favor quantity or novelty. #ai #music #artificialintelligence #musicindustry

Two leading AI music companies are causing controversy. The similarities tell us a lot. - Suno has released their Gen AI product. You can create astonishingly good full-length songs, including lyrics (via their ChatGPT integration). - And Jammable has been called out by the Recording Industry Association of America® (RIAA) for offering over 3000 unlicensed vocal models of top artists. The issues have to do with how each company generates their content. In Suno's case, they have clearly used copyrighted IP in their proprietary model (although the company won't say definitively). And Jammable is straight-up scraping YouTube to make their vocal models. It seems intuitive that a startup shouldn't be able to take a music catalog, then create new music based upon it without credit or payment. And it seems even *more* intuitive that a company shouldn't be able to rip Beyoncé's voice on YouTube, then commercialize it. But right now, both of these situations are not illegal. And whether or not it is even ethical is also up for debate. This tech is here and it is getting more & more sophisticated. As the industry reconciles with it all, we need guardrails & consensus. We do not have either right now. #musicindustry #musicbusiness #musicAI #genAI

🎵 YouTube and Universal Music Group have reached an agreement over a framework for managing AI-generated music: In collaboration with music labels, YouTube published "AI music principles" - guidelines governing the treatment of AI-generated music on its platform. They've laid down the framework for managing AI-generated music, encapsulated in three fundamental principles: 1️⃣ Responsible AI Adoption: YouTube commits to embracing AI technology responsibly in collaboration with its music partners. 2️⃣ Balancing Creativity and Protection: The platform recognizes AI's potential to revolutionize creative expression but emphasizes the importance of safeguards to protect artists and their work. 3️⃣ Trusted Framework: Leveraging its industry-leading trust and safety organization, YouTube aims to extend its content policies to regulate AI-generated content effectively. Along with the guidelines, Youtube launched an AI Music Incubator, where artists can experiment with AI-generated music tools. While there remain concerns for copyright owners, CEO Neal Mohan has shared his intent to ensure robust copyright protection. 🌐 https://lnkd.in/gSBwQdQu

The biggest AI pioneer in music right now: Grimes. Through her AI venture, elf.tech, the Canadian singer has been licensing her own content to allow anyone to create their own songs using her voice. In exchange, she gets a 50/50 split of revenue from streams of tracks created with her voice AI. This move is groundbreaking, for 2 reasons: 1. It tests the waters on whether enabling anyone to use AI to replicate your unique voice & sound can truly change the way music is made (and monetized). 2. It demonstrates a burgeoning consumer appetite for AI-generated music – the GrimesAI song "Cold Touch" by Kito has nearly 2 million streams. What does this mean for the industry? If Grimes' venture succeeds, it points to a lucrative new path for artists. Will it kill music as we know it? I don’t think so. There will always still be something irreplaceable about knowing the human behind the song. Artists are storytellers. And the best artists take their fans on a journey with every song and album they release. That feeling of being able to relate to the artist behind the record is something AI can’t replace. But it isn’t binary. Music as we know it and a new form of AI-generated music will co-exist. After all, country, rap, and rock are huge genres. But so is EDM… AI is changing entertainment as we know it. Follow along Nick M.. https://lnkd.in/d2WxpWvN