Spotify’s $75 million drain: How algorithm-generated spam steals royalties from human artists

Imagine being a musician. After months sometimes years of relentless dedication, late nights, and creative sacrifice, you finally craft a piece of music that truly reflects your identity and passion. You upload it to Spotify, trusting that this global digital stage will connect you with listeners around the world and provide a fair source of income. At first, everything feels right.

Streams slowly start to come in, Spotify playlists begin to pick up your track, and you watch your audience grow through Spotify’s discovery system. Over time, those Spotify royalties become more than just numbers on a dashboard they turn into a lifeline, something you begin to rely on to sustain your career and keep creating the music you love.

Now imagine opening your royalty statement and seeing it quietly shrink not because your audience disappeared, not due to piracy, and not because another artist outperformed you but because the system itself has been flooded. A massive, invisible wave of fraudulent, algorithmically generated tracks is being uploaded at scale, designed not to be heard or loved, but to game the platform’s algorithms.

These artificial songs siphon attention, manipulate streams, and dilute the entire royalty pool. As a result, your genuine work earns less, even though you did everything right. In this new reality, creativity competes not with talent, but with automation and the cost is borne by real musicians whose livelihoods are slowly eroded by something they cannot see or control.

This is the grim reality of the AI content flood hitting the music industry.

In recent reports, Spotify revealed it had scrubbed over 75 million “spammy” or fraudulent tracks from its system in a single year. To grasp the enormity: the total legitimate music catalog on Spotify is only around 100 million songs. The volume of digital junk nearly overwhelmed the platform.

Though the exact financial toll remains difficult to measure with precision, industry analysts broadly agree that the scale of this problem is staggering. Estimates suggest that fraudulent activity fueled by mass-produced, AI-generated tracks is illegally rerouting as much as $75 million every year from the collective royalty pools that are intended to support authentic, human creators.

This money does not disappear in isolation it is siphoned directly from a shared system, meaning every fake stream marginally reduces the payout for legitimate artists. For independent musicians who already operate on thin margins, even small losses can have a significant impact on their ability to fund recording sessions, marketing, touring, or future projects. Over time, this silent diversion of funds distorts the economics of streaming, rewarding scale and automation over creativity and effort, and placing real artists at an unfair and increasingly unsustainable disadvantage.

This is more than just a technological nuisance; it’s a calculated act of digital asset theft and systemic deception.

Also read: The RPA revolution: Automating mundane tasks without writing code

What motivates bad actors to inundate streaming platforms with mountains of low-effort, AI-created ambient noise, sound effects, and short loops?

The incentive is simple: The Streaming Payout Mechanism.

1. The threshold: On platforms like Spotify, a track is considered “played” and becomes royalty-eligible after just 30 seconds of listening, a rule originally designed to fairly compensate artists while keeping the user experience simple. However, this relatively short threshold also creates a structural vulnerability within the streaming model.

It allows artificial or automated listening systems to generate massive numbers of qualifying streams without any real human engagement or appreciation of the music itself. As a result, tracks can accumulate royalties based purely on technical compliance rather than genuine listener interest. While this system works reasonably well for organic discovery and casual listening, it becomes problematic when exploited at scale, enabling fraudulent actors to manipulate play counts, inflate visibility, and siphon money from the same royalty pool that legitimate artists depend on for their livelihood.

2. The production: Generative AI tools allow scammers to instantaneously create thousands of so-called “functional” music pieces such as background music, ambient soundscapes, meditation tracks, or even deepfaked voice clones at virtually zero cost and with minimal human effort. These tracks are often designed not to be memorable or artistically expressive, but to blend seamlessly into playlists where passive listening is common.

By flooding streaming platforms with this mass-produced content, bad actors can exploit recommendation systems and streaming thresholds, generating large volumes of plays without attracting scrutiny. The result is an industrial-scale operation that prioritizes quantity over creativity, enabling fraudulent earnings while undermining the value of genuine musical craftsmanship and further straining the already competitive ecosystem for real artists.

3. The operation: Instead of relying on real human listeners, fraudsters turn to large-scale bot farms vast networks of simulated or compromised user accounts programmed to behave like genuine users to repeatedly hit that critical 30-second listening threshold. These automated systems can trigger qualifying plays millions of times across thousands of tracks, all without any authentic engagement.

In many cases, the music itself is deliberately engineered to be just slightly longer than the minimum requirement, ensuring that each automated listen counts toward royalties while consuming the least possible time and resources. This calculated efficiency allows scammers to maximize fraudulent payouts at scale, overwhelming detection systems and further distorting the royalty distribution that legitimate artists depend on to survive.

4. The dilution: Since streaming platforms distribute a large, shared royalty pool based on each artist’s proportion of total streams, the system is inherently zero-sum. Every play generated by a bot does not create new value; instead, it quietly takes a slice of the existing pool.

That means each fraudulent stream directly reduces the amount of revenue that would have otherwise gone to a real human artist based on their legitimate listener engagement. As bot-driven plays scale into the millions, the cumulative impact becomes severe shrinking payouts across the board, even for artists with loyal audiences and consistent growth. Over time, this distortion penalizes authenticity and effort, rewarding manipulation while making it increasingly difficult for genuine creators to earn a fair return from their work.

This sequence represents a direct, automated shift of economic power away from legitimate creators toward sophisticated digital content manipulators.

The damage extends beyond mere financial loss. The AI content flood actively poisons the user experience and damages the integrity of the music discovery process:

• The content sludge: Spotify has acknowledged that generative AI is being used by “bad actors and content farms to confuse or deceive listeners, and push ‘slop’ into the ecosystem”. This deluge of low-quality soundscapes and repetitive loops clogs search results and low-attention playlists (e.g., “Relaxing Sounds”).
• The algorithm break: As these fraudulent streams accumulate, they begin to skew the platform’s recommendation algorithms. A user listening to an ambient playlist may suddenly be fed a steady diet of bot-farmed music instead of tracks from genuine, independent musicians, locking listeners into a cycle of inauthentic content.
• Identity theft: The most dangerous tactic involves the unauthorized use of AI voice clones (audio deepfakes) to impersonate established, recognizable artists, resulting in consumer deception and intellectual property infringement.

AI provides the capacity to mimic the sound of music without the heart of human artistry, leveraging platform tools to promote fraudulent activity.

Spotify’s defense: An ongoing battle

Spotify is actively addressing this growing crisis, signaling that the threat is neither hypothetical nor minor. The removal of 75 million spam tracks in a single year highlights just how widespread and deeply embedded fraudulent activity has become within the platform. This unprecedented cleanup effort underscores both the severity of the challenge and the immense scale at which bad actors have been operating.

At the same time, it reflects Spotify’s recognition that unchecked abuse can undermine trust in the streaming ecosystem and harm legitimate artists. While removing tens of millions of tracks is a significant step, it also illustrates how persistent and adaptive these schemes are, reinforcing the need for ongoing detection, stricter safeguards, and systemic changes to protect genuine creativity and ensure fair compensation.

Key measures being deployed include:

• Advanced filtering: Deploying a new, sophisticated system designed to identify and block mass uploaders, suspiciously similar content, and tracks that manipulate search result rankings.
• Stricter policy on deepfakes: Explicitly prohibiting the unauthorized use of AI to clone artists’ voices, providing clearer grounds for takedowns and legal action.
• Transparency requirements: Pushing for new industry metadata standards that mandate disclosure from artists and distributors regarding the use of AI in track creation.
• Payout barriers: Instituting a new minimum threshold requiring tracks to accumulate at least 1,000 streams before becoming eligible for royalty payouts, a tactic designed to discourage the automated generation of endless micro-stream tracks.

The fight against AI content fraud is a pivotal moment for the streaming industry. If automated, fraudulent tracks are allowed to continue draining the global royalty pool, the consequences will go far beyond isolated cases of abuse and strike at the very heart of the music ecosystem. The already fragile financial foundation that supports small and emerging human artists will steadily erode, making it increasingly difficult for genuine creators to earn a sustainable income from their work.

As artificial streams inflate numbers and redirect payouts, real musicians who invest time, emotion, and lived experience into their art will find their earnings on Spotify steadily shrinking despite loyal audiences and consistent engagement. When manipulation distorts Spotify’s streaming metrics, it undermines the trust that artists place in the platform as a fair marketplace for creativity.

Protecting Spotify’s creative environment is therefore not just a technical necessity, but a cultural responsibility. Without strong safeguards, authenticity on Spotify risks being overshadowed by sheer volume and algorithmic manipulation, discouraging new and emerging talent from entering the space at all. Ensuring fair distribution, accountability, and transparency within Spotify’s royalty system is essential if real, human-made music is to continue thriving, evolving, and resonating with listeners around the world.