The AI detection tools protecting music’s future

As AI-generated music advances at an unprecedented rate, so too does the need for tools that can discern human-composed tracks from machine-made creations. Companies like Ircam Amplify are at the forefront of this movement, having developed an AI music detector that can authenticate music and help music industry stakeholders make the difference. In this article, we’ll explore why AI music detectors are essential to the future of the music industry, how these tools are poised to evolve in the coming years and who the top players in this field are today.

The top AI music detection tools to follow in 2025

Ircam Amplify’s AI music detector

Ircam Amplify’s AI music detector is one of the most promising technologies in this space. By using machine learning algorithms trained on vast music datasets, the tool is able to tag AI-generated tracks at scale. This promises to be a powerful solution for rights holders and music industry stakeholders such as music supervisors looking for human music to sync in their next audiovisual project. Indeed, this kind of technology would allow them to make the difference between artificial and genuine creation.

YouTube Content ID by Google

In September of 2024, YouTube announced its new synthetic-singing identification technology, a tool that will enable creators to detect AI-generated content on YouTube that simulates their voices. This technology is set to be added to YouTube’s existing Content ID system in 2025, one that has already been highly effective in identifying copyrighted content on the platform.

Audible Magic

Audible Magic’s Version ID tool leverages patented AI technology to recognize cover songs, live performances, and even AI-generated or transformed versions of songs, like parodies and acoustic renditions. By analyzing multiple musical elements such as melody, structure, lyrics and more, this AI music detector can identify alternate song versions that differ from the original recording, thus helping music industry stakeholders keep track of their work’s use and make sure that all the appropriate licensing and copyright compliance rules are being followed.

Believe’s AI Radar

In 2023, Believe announced the launch of its internal AI detector called AI Radar, capable of determining if a piece of music has been entirely created by artificial intelligence. With an accuracy rate of 98% for AI-generated recordings and 93% for deep fakes as of november 2023, this tool aims to address growing concerns about copyright in the music industry. It represents a significant advancement in protecting artists and maintaining the integrity of musical content in an increasingly AI-driven era.

Why the music industry needs AI music detectors

Copyright protection and monetization

As AI technology continues to drive the creation of new, sophisticated music, distinguishing between AI-generated and human-composed content becomes essential for copyright management. These tools help ensure that each piece of music can be accurately attributed to its creator, whether human or AI, securing fair compensation and legal protection for artists, labels, and publishers.

Without proper detection, AI-generated music could crowd streaming platforms, inadvertently reducing royalties for human creators.

Indeed, most streaming platforms today are based on a “pro-rata” or “shared pool” revenue model. This means the total revenue generated from paid subscribers and advertisers on streaming platforms is pooled together and then distributed to artists based on their percentage share of total streams. In a pro-rata system, when AI-generated music quickly fills streaming platforms due to its low production costs and racks up streams, the revenue per stream decreases across the board, leaving less money for each human artist. Even if an AI track gets a million streams and a human artist also gets a million, the total earnings per stream are diluted when AI music occupies a larger share of streams. Thus, the presence of AI content potentially decreases the earnings for human artists, even if their stream count remains steady.

AI music detectors like the one developed by Ircam Amplify allow streaming platforms to distinguish human-made music from music generated by AI, thus enabling them to explore alternative and effective payout models that preserve higher earnings for human artists. This is something that the streaming platform Deezer has already started experimenting with using its own AI music detection technology.

Authenticity and artistic integrity

One of the most intangible yet crucial aspects of music for listeners is its authenticity and how it speaks the intricacies of their own humanity. People want to hear from people, and fans usually connect with the artist themselves, just as much as their work.

As AI compositions become increasingly capable of mimicking popular music styles, the line between human and machine creativity can blur. AI music detectors preserve an artist’s creative integrity, authenticity and the human connection they have with their fans by allowing audiences to know what they’re listening to and where it comes from.

AI music detectors will likely become particularly relevant in the world of music synchronization where music supervisors may actively want to find human-made music in their film, TV show, advert or video game, as a means of elevating the work’s emotional and narrative impact.

On Bridge Sync, Bridge.audio’s commission-free sync marketplace, music buyers can already use Bridge’s powerful AI music analyzer to search for human-made music by genre, mood, vocal type, instrumentation, lyric theme, language and more. Bridge Sync’s catalog now includes over 100,000 tracks from more than 250 labels and publishers including Allo Floride Publishing, Velvetica Publishing, Tôt ou Tard, Jansen Records, Baco Publishing, and more.

Risk management for labels and publishers

For music labels and publishers, the legal and financial implications of unregulated AI-generated content can be significant. Undetected AI tracks could lead to copyright disputes, especially if machine-generated songs inadvertently resemble copyrighted works.

AI-detection technology offers a layer of protection by identifying potential issues before they escalate. This is especially relevant in cases where AI-generated tracks use synthetic voices of well-known artists or replicate copyrighted material without permission, an area that streaming services like Deezer are actively working to monitor. Accurate AI detection thus helps labels and publishers avoid potential financial losses, maintain their reputation, and comply with copyright laws by catching potential infringements early on.

In summary, these detection tools are more than technical innovations, they’re essential to managing the complexities AI has introduced to the music industry. By addressing copyright, maintaining authenticity, and mitigating risks, they support a healthier ecosystem for artists, labels, and audiences alike.

What the future holds for AI music detectors

Looking ahead, AI music detectors are likely to become increasingly sophisticated, integrating into various stages of music creation, licensing, and distribution. Here are some of the evolutions we can expect:

Improvements in detection accuracy: As machine learning models are trained on ever-expanding datasets, detection accuracy will improve. Future iterations of these tools could become adept at identifying more subtle, nuanced patterns that distinguish AI compositions, reducing false positives and creating greater confidence for rights holders and other music industry stakeholders.

Expansion into real-time detection: Real-time detection could soon be a reality, enabling AI music detector tools to analyze music live on streaming platforms, radio broadcasts, and even concerts. Real-time analysis would be a game-changer, allowing for immediate identification of unauthorized AI-generated tracks and ensuring live audiences experience authentic, unaltered performances.

Integration with blockchain for rights management: Blockchain could play a significant role in the future of AI detection, providing an immutable record of each track’s history, edits, and ownership. By linking AI music detectors with blockchain-based rights management, it becomes easier to trace a track’s origins and establish its legitimacy, thus building a foundation for fairer compensation and licensing practices.

Challenges facing AI detection in music

While promising, AI-detection technologies face notable hurdles:

Constant evolution of AI and deepfakes: As AI generation capabilities advance, so do the techniques to bypass detection. Maintaining effective detection tools will require constant updates to keep pace with the evolution of AI in music.

Privacy and ethical considerations: Widespread implementation of AI-detection tools raises concerns around privacy, especially when scanning content en masse. Striking a balance between protection and privacy will be essential to avoid encroaching on individual rights or unintentionally stifling creative freedom.

Fair Compensation Models: With the rise of AI-generated music, equitable compensation models are increasingly important. AI-detection tools alone cannot address compensation issues, but by ensuring proper attribution, they create the foundation for more inclusive compensation models in a future where both human and AI creations coexist.

Conclusion

AI music detectors are more than just a safeguard, they’re integral to maintaining a sustainable and fair music ecosystem. As AI-generated music continues to reshape the music industry, it’s essential for music professionals to understand these technologies’ potential and support their ethical development. By embracing these technologies, music industry professionals can protect the value of human-made work, preserve the uniqueness of human artistry, and adapt confidently to a future where AI and humanity meet harmoniously.