The news: Fraudulent streaming is siphoning royalties from human artists, complicating ad targeting for marketers, and leading consumers to listen to AI-generated music without their knowledge.

In a conversation with EMARKETER, HUMAN Security senior threat intel analyst Inna Vasilyeva and vice president of threat intelligence Lindsay Kaye highlighted how this fraud is changing the streaming landscape and posing risks to artists, listeners, and brands alike.

How it works: Bad actors craft troves of genAI music, sometimes millions of tracks. The skills, time, and resources needed to create this content no longer serve as obstacles—AI tools like Suno, Udio, and ElevenLabs allow full songs with instrumentals, vocals, and lyrics to be generated from a single prompt.

• The music is often bland or repetitive, per HUMAN, and typically uploaded to multiple streaming platforms under fake artist profiles with no real musician behind the content. In fact, 70% of AI-generated songs examined by HUMAN that claimed to come from human artists were fully genAI and not recorded by real musicians.
• Scammers then generate fake traffic and engagement to make the content seem legitimate through tactics like bots, click farms, and playlist manipulation.

Why it matters for advertisers: Fraudulent genAI content can degrade users’ streaming experience and make it harder for advertisers to accurately plan campaigns since they may not know what user data is legitimate, Vasilyeva said.

• Marketers risk wasting ad spend on corrupted data influenced by the vast numbers of bots boosting fraudulent content’s listening stats, eroding opportunities to target ads on a micro level, she said.
• “It's just making it even harder to get the legitimate content and legitimate eyes in a sea (of) AI,” Kaye added.

Why it matters to streamers: For Spotify, Apple Music, and other platforms that focus on personalization, fraudulent engagement can mistrain recommendation models and serve users irrelevant or low-quality music while pushing legitimate artists out of visibility.

If listeners repeatedly encounter AI filler tracks or generic genAI content, they may switch platforms or spend less time streaming altogether. This dynamic undermines platform integrity and threatens revenue models, since advertising and subscription retention both depend on data quality and user engagement.

What brands should do: With data quality and trust serving as major elements of campaign deployment and optimization, brands must demand transparency from streaming platforms and prioritize verified ad inventory.

• Working with companies like HUMAN that provide bot detection or traffic validation tools can help ensure ads reach real ears.
• Cross-channel measurement to compare engagement across platforms will help identify anomalies and inflated performance metrics tied to fake activity.

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