Introduction to AI Music Concerns
In mid-2025, frustration reached a peak for Cedrik Sixtus, a software developer based in Leipzig. He noticed that his Spotify playlists were increasingly populated with tracks he suspected to be AI-generated. To address this, he created a tool that automatically labels and blocks such tracks from his listening experience.
Sixtus shared his Spotify AI Blocker on several code-sharing platforms, where it has been downloaded by hundreds of users. The tool filters out a growing list of over 4,700 suspected AI artists. It relies on community tracking efforts and indicators such as unusually high release volumes and AI-style cover art, supplemented by external detection tools.
"It is about choice – if you want to hear AI music or if you don't,"
"I would prefer Spotify labelled and enabled filtering of AI-generated content itself,"
Sixtus's tool is initially installed through the web browser version of Spotify. However, he cautions users that employing his software
"may violate Spotify's terms of service".
He is not alone in his concerns; the community forum of Spotify, the world's most popular music streaming service, reflects strong feelings on this issue. While Sixtus finds AI music unsatisfactory in sound quality, others simply do not want to listen to music created by bots.
Spotify's Response and Industry Challenges
Spotify has taken some steps to address these concerns. In April 2025, it launched a test feature that displays, within a song's credits, how an artist has used AI. This system is voluntary and depends on artists disclosing AI use to their record labels or distributors.
"We know this isn't a complete solution on its own. Building a truly comprehensive system is a challenge that requires industry-wide alignment,"
Spotify's stance is far from actively identifying AI-generated music and providing users with filtering options. Robert Prey, a researcher at Oxford University's Internet Institute who studies streaming platforms, describes Spotify's position as a
"difficult – borderline existential – balancing act".
Spotify aims to avoid making value judgments about music creation methods but risks undermining trust among listeners, artists, and the broader industry if it lacks transparency. Prey explains,
"It has to figure out what listeners want and how artists feel – all while AI is improving, being used more widely and becoming harder to detect."
The Rise of AI Music and Its Impact
The emergence of AI tools for music creation is both enticing and unsettling the music industry. Generative AI music services such as Suno and Udio now produce polished, fully realized songs complete with lyrics, vocals, and instrumentation from simple text prompts within seconds.
In a recent controlled test conducted as part of a Deezer–Ipsos poll, 97% of listeners failed to correctly distinguish between AI-generated and human-made tracks. Tens of thousands of AI tracks are reportedly uploaded daily to streaming platforms, potentially diluting revenue for human artists, although most currently receive few listens.
Spotify, along with YouTube Music and Amazon Music, has so far refrained from implementing clear user-facing labels or filters for AI-generated music. They neither openly use detection tools nor require systematic self-disclosure, though this may evolve as industry standards develop.
Artists widely suspected to be AI-generated, such as Sienna Rose, Breaking Rust, and The Velvet Sundown, are treated like any other artists by Spotify. However, the platform does remove what it considers AI-related spam, including mass uploads and short tracks designed to manipulate the system.
"Our priority is addressing harmful uses [of AI] like spam and impersonation, rather than trying to filter music based on how it was made,"
a Spotify spokesperson said, adding that AI in music is not a binary category but exists on a spectrum.
Deezer’s Approach to AI Music
Deezer, a smaller competitor to Spotify, has adopted a more assertive approach. In 2024, it began tagging albums containing AI-generated tracks produced by services like Suno and Udio and excluding these tracks from algorithmic recommendations and human-made playlists.
Deezer employs its own in-house detection technology, which trains AI models to identify statistical patterns in the sound itself. The company recently started offering this technology for sale across the industry.
"We're the only music streaming platform that has that in place,"
notes Jesper Wendel, Deezer's head of global communications.
Apple Music and Transparency Tags
In March 2025, Apple Music announced it would introduce "transparency tags" and eventually require music labels and distributors to self-disclose when new songs or related content involve AI. However, critics argue these measures may not be reliable, as artists might avoid disclosing AI use due to stigma. Additionally, how prominently Apple's tags will be displayed to listeners remains unclear.
Complexities of Labeling AI Music
Maya Ackerman, an expert in AI and computational creativity at Santa Clara University and CEO of WaveAI, explains that AI music exists on a continuum, complicating labeling efforts. Some tools operate on a "prompt in, song out" basis, where labeling AI music is straightforward. Others assist musicians in co-creation, contributing to specific parts of the music-making process.
Ackerman questions,
"If a musician uses those tools, at what point does that warrant a label?"She adds that even with tools like Suno and Udio, users often invest significant creative input, such as providing lyrics or iterating extensively on the song's sound.
"From a distance it looks like such an obvious 'yes, label AI music' but, once you zoom in, you realise it is a very complicated thing,"
she says.
Technical Challenges in Detecting AI Music
Detecting AI-generated tracks accurately is technically challenging and carries risks of falsely labeling human musicians as AI-generated. Bob Sturm, a researcher at the KTH Royal Institute of Technology in Sweden, notes that AI detection systems are trained on outputs from existing AI music generation tools. As these tools improve, detection software must be continuously retrained, creating an "AI music arms race."
Manuel Moussallum, Deezer's head of research, acknowledges the challenge but states that Deezer's detection technology has maintained a low false positive rate. Research continues to better understand hybrid cases where AI is partially used.
Debate Over Labeling and Filtering
Some experts view concerns about labeling as a distraction. David Hoffman, a professor at Duke University studying AI's impact on artists' livelihoods, criticizes the argument that the complexity of labeling justifies inaction.
"There is a lobbying message to say 'we can't draw the line, and therefore we shouldn't do anything',"
he says. Hoffman advocates that platforms should at least label fully AI-generated tracks and then evaluate the broader issue.
Listeners also appear to favor labeling. In the Deezer–Ipsos poll, approximately 80% of respondents supported clear labeling of AI-generated music, though opinions on filtering were more divided.
"Listeners deserve awareness,"
singer-songwriter Tift Merritt, who collaborates with Hoffman as a practitioner-in-residence at Duke, emphasizes, citing the analogy of nutritional labels on food or organic certifications.
Economic Considerations and Platform Incentives
Many speculate that economic factors may be the primary reason Spotify has not embraced labeling and filtering AI music. Robert Prey from Oxford suggests Spotify prioritizes platform growth by keeping recommendation systems as "unencumbered and free to operate as possible."
David Hoffman notes that detecting AI-generated content adds costs and that serving AI music might be cheaper for the platform. Past controversies fuel skepticism; Spotify has faced accusations of commissioning and promoting lower-cost music for background playlists, which it denies.
"All tracks on our platform are delivered by third-party rightsholders like labels and distributors, and the payment model is the same for all of them: royalties are paid out of the revenue pool based on listening share,"
a Spotify spokesperson said.
Future Outlook and Industry Standards
The situation is evolving. The music industry's standards body, DDEX, continues to develop a broad industry standard for AI disclosures in music credits, though how these will be displayed depends on streaming platforms.
Under the EU AI Act, certain AI-generated content must be labeled starting August 2026, but how Spotify will implement these regulations remains unclear.
David Hesmondhalgh, professor of media, music, and culture at the University of Leeds, describes the current state of AI music as a "Wild West" but anticipates that
"some kind of order will emerge,"similar to how the early-2000s file-sharing crisis led to today's streaming industry.
Spotify appears to recognize the growing pressure. It recently announced features aimed at highlighting human artistry, including SongDNA and "About the Song," which provide premium users with deeper insights into a track's origins and contributors.
"We believe the right response to AI in music isn't any single policy, it's a combination of proactive controls, industry-wide standards, and a deeper investment in the human creativity behind every track,"
added the Spotify spokesperson.
