The flood of AI-generated content has hit the music industry hard and fast. The number of fully AI-created tracks uploaded daily to Deezer’s streaming music platform reportedly jumped from roughly 10,000 in January 2025 to more than 50,000 in November, accounting for more than 34% of all daily new uploads. Last year, the “band” Velvet Sundown racked up more than 1 million streams on Spotify in a matter of weeks before it came to light that everything about it was AI-generated: its music, promotional images, and origin story. “Heart on My Sleeve,” a track that supposedly featured megastars Drake and the Weeknd, garnered millions of plays across online platforms in 2023; turns out, it was an AI imitation created by an anonymous person.

Left unchecked, the rise of generative AI will be music’s next Napster moment—an industry-shaking event that will likely ripple for years, with time measured in BC (Before ChatGPT) and AC. When someone can produce a viral hit with nothing more than inexpensive AI software and a touch of marketing savvy, then music artists, publishers and record labels, digital service providers (DSPs), and other industry stakeholders are right to grapple with existential questions about generative AI’s effect on their livelihoods and what they can and should do about it.

Still, before industry stakeholders curl into a ball and play Bill Withers’ “Ain’t No Sunshine” on repeat, it’s worth remembering that music has survived and thrived through many a technological disruption over the past 150 years, from the phonograph to electric guitars to digital audio workstations.

Furthermore, music fans still put a huge premium on human artistry and authentic connections with artists, and that’s unlikely to change anytime soon. About 62% of US consumers say they’re less likely to or would not engage at all with music that was generated in whole or in part by AI, according to Bain’s 2025 Media Consumption Survey (see Figure 1). That was one of the strongest endorsements of human-created content across media types.

Figure 1

At the same time, just as with books and other media, most consumers are open to artists using AI as a creative tool—for example, to help with initial song development or to enhance the sound of instruments or vocals (see Figure 2).

Figure 2

The key will be harnessing the technology and striking the right balance. As the enigmatic music legend and innovator Bob Dylan put it in a 2022 interview, technology “can hamper creativity, or it can lend a helping hand and be an assistant.” It might help “get you over the hump, but you have to get up early,” he continued. The industry leaders that “get up early”—moving quickly to embrace generative AI as a complementary tool while investing in human artists and diligently protecting their intellectual property—have a chance to lead the way in this new era.

“Standin’ at the crossroad”

The music industry was already at a crossroads when generative AI arrived. On one hand, people are listening to more music than ever. Music has always been the soundtrack to our lives, but it’s easier than ever to play that soundtrack throughout the day, thanks to ever-present technology: music streaming, smartphones, Bluetooth-enabled earbuds, and improved WiFi and 5G coverage. Music moves culture, helping us find common ground and influencing what we wear, how we talk, and what we talk about. 

On the other hand, the streaming business model isn’t evolving fast enough to keep pace. On-demand song streams more than quadrupled worldwide between 2017 and 2023, but revenue per stream fell by about 30% during that period. Monetization lagging consumption was somewhat expected, as the share of new paid music subscribers shifts from established to developing music markets in which the industry generates less revenue per user on average. But the industry has played its part in the monetization challenge, too, with slow price increases, limited customer segmentation, insufficient policing of fraud and copyright infringement, and a lack of innovative new products and experiences for superfans.

Generative AI will continue to exacerbate some of these challenges. Bad actors can use it to create fraudulent music more quickly and inexpensively than ever, while making it harder to protect copyrights and trace song attributions. The technology will upend song economics for certain segments of the market. For example, it will provide a low-cost, royalty-free alternative for companies that commission and license production music (e.g., for film, TV, video games, advertising, and mobile apps) as well as for DSPs’ increasingly popular lifestyle offerings (think sleep and study music, or ambient sounds).

That said, generative AI also has the potential to unlock new creative frontiers for artists and more personalized ways to engage with their fans. It could also enable their partners to meet fans where they are with more authentic and immersive experiences. 

“The times they are a-changin’”

As with any disruptive technology, industry profit pools will shift as new competitors rise and take share from incumbents. Some will adapt to change better than others. Here are some of the most important success factors for companies and stakeholders across the music value chain.

Creators

Generative AI will elevate established creators’ artistry, providing another tool to help them work faster, experiment more, and push creative boundaries. By lowering the barriers to making music, the technology will simultaneously enable a new class of creators (will a new AI-generated music genre emerge?) and unleash a flood of hobbyists. Only a small subset of this music will break through the noise and compete with established professional artists, but those artists still must adapt.

It’s all about staying relevant and top of mind among fans. Releasing more music more frequently will be an important part of the answer; it can boost artists’ positioning within DSP algorithms, curated playlists, and recommendation feeds, while fostering continuous connection with fans and building anticipation for new content.

Each artist will need to decide how much to embrace generative AI. In some genres, such as dance and electronic music, leaning into generative AI for music creation will feel like a natural evolution that fans will likely accept or even reward. In others, such as folk or indie rock, artists may want to avoid generative AI altogether as part of their brand, or only deploy it subtly for technical support such as mixing and editing. All artists face a high-stakes strategic choice whether to license their music to train generative AI models and allow it to be sampled, remixed, or rearranged in AI-generated music.

Music publishers and record labels

Faced with another disruptive technology, executives recognize that running their Spotify playbook—not the Napster one—will serve them best this time around. That means helping to steer generative AI in music, not squash it, while fiercely protecting the value of human artistry and intellectual property. A big part of that will be investing in new technologies that enable song attribution tracing and fingerprinting.

Generative AI also opens exciting possibilities for publishers and labels, and not just in areas such as marketing or operational efficiency. They could use AI-powered tools to empower fan creativity and engagement, such as apps that allow consumers to legally remix clips of popular songs. For example, Universal Music Group recently announced a strategic agreement with Udio that allows subscribers to use authorized and licensed UMG music to customize, stream, and share music responsibly on the Udio platform. AI could even expand artists’ fan bases (e.g., translating an artist’s recorded vocals into other languages) and extend artists’ recording and touring careers (e.g., using generative AI to help an older singer’s voice sound and perform like it did years earlier).

Royalty collection management organizations (CMOs)

The threat of generative AI accelerating copyright infringement and fraud is urgent for this group. Ironically, CMOs can also use generative AI to improve their technology systems for royalty collections, database management, and payment distributions to publishers and artists. Leading CMOs will partner with publishers and labels to protect music IP, such as by engaging constructively with policymakers and supporting companies investing in music attribution technologies. They will also seek out new growth opportunities that leverage their data or unique position in the ecosystem as trusted “third parties.” Like publishers and labels, CMOs will also pursue AI-enabled operational efficiencies and cost savings, which can be reinvested or distributed to creators.

DSPs

The last decade of music streaming growth was defined by scaling up an immensely popular product around the world while keeping prices relatively stable. The next phase will likely involve more customer segmentation, premium tiers for superfans, and innovative new offerings. If done well, this will result in greater differentiation among DSPs, better products for fans, and increased royalties for rightsholders.

The pressure to evolve will only grow as agentic AI advances. AI agents could create new competition and potentially an existential threat to traditional DSPs if music rightsholders strike deals directly with AI companies and new generative AI–native DSPs.

Incumbents’ approach to generative AI music will play a major role in their differentiation between each other and vs. new upstarts. Spotify recently announced a partnership with major labels, publishers, and industry service providers to develop generative AI tools that empower artists and help them connect with fans. Meanwhile, Deezer says it now prominently labels AI-generated tracks and excludes them from algorithmic recommendations and editorial-curated playlists. Will other streaming music platforms follow suit? What about tagging AI artists? Or will some incumbents make generative AI less of a focal point, embracing and financially rewarding human artistry even more?

The right answer will vary based on each DSP’s customer base, brand, and capabilities. Regardless of which strategy they take to sourcing, classifying, and promoting different types of music, generative AI will become a vital aid for understanding fans and delivering the more immersive and interactive experience that many seek. In our survey, 28% of US music listeners under age 18 said they also create music, as do 14% of 18-to-24-year-olds. DSPs can strengthen their competitive position by leaning into this consumer-creator trend and giving users more tools to create, share, and discuss content.

Live music companies

The magic of live, in-person concerts—and the human connections they forge—can never be replicated or replaced by technology. That said, we believe current AI technology can augment the existing in-person concert experience—think instant voice de-aging to extend touring careers, improved and lower-cost audio visuals synced to music, or better sound mixing to match the venue acoustics.

In addition, AI could eventually enable new live experiences that can extend the reach of artists and create new revenue streams. A number of innovative studios are already using advanced digital technologies to create immersive live entertainment environments and new types of live music experiences, such as ABBA’s digital avatar shows. Generative AI could reduce costs and improve the latency and reliability of tech-enabled experiences, opening new creative avenues.

“Eye of a hurricane”

Generative AI could wind up being one of the most disruptive technologies in music history, changing how music gets written, produced, marketed, and distributed. But it doesn’t spell the end of the industry, just the beginning of a new era. The creators and companies that accept that and move swiftly to capitalize will have a shot at enduring success. So, put on R.E.M.’s “It’s the End of the World as We Know It (And I Feel Fine),” crank up the volume, and roll up your sleeves.