AI Is Rewriting the Music Playbook: What Labels Need to Know Right Now

The music industry has always evolved through moments of disruption. Vinyl gave way to streaming. MTV gave way to TikTok. But no shift has felt as sudden and complex as the rise of artificial intelligence.

Over the past few weeks, three major stories have shaken the industry: Spotify’s removal of 75 million “spam” tracks, Sweden’s introduction of a licensing model for AI music training, and the launch of Sora 2, OpenAI’s new generative video platform. Each of these stories highlights a different side of the same reality. AI is not a distant possibility. It is already reshaping how music is created, distributed, and experienced. For labels, the question is no longer whether to engage with AI, but how to do so intelligently.

AI in the Music Industry: Spotify’s Spam Crackdown - A Wake-Up Call for the Streaming Era

In late September, Spotify announced that it had removed 75 million tracks from its platform that were identified as AI-generated spam. Many of these tracks were produced to game the system through low-effort loops uploaded in bulk to collect streaming royalties. Spam tactics such as mass uploads and large volumes of low-quality tracks are increasingly used to exploit streaming platforms, prompting the development of music spam filters designed to identify uploaders who generate large volumes of content for manipulation.

The scale of this purge signals a deeper problem. As AI tools for music generation become more accessible, the volume of low-quality or manipulative uploads is skyrocketing. These practices not only harm the discovery and compensation of professional artists but also threaten the integrity of the music ecosystem by enabling bad actors to generate large volumes of content through spam tactics. This not only clogs streaming platforms but also dilutes royalty pools, making it harder for legitimate artists to be discovered and paid fairly.

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Why it matters for labels:

• Catalog integrity is at stake. Labels have spent decades building rosters and catalogs. An environment flooded with AI slop threatens the value of legitimate music and risks overshadowing the work of authentic artists, making it crucial to protect their contributions from being devalued by AI-generated spam.
• Discovery gets noisier. Algorithms thrive on volume. If AI-generated spam overwhelms platforms, human artists may struggle to break through.
• Monetization models are vulnerable. Royalty dilution affects everyone, from indie artists to major labels, and will likely accelerate changes to how streaming revenue is allocated.

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Influur’s take:

This is not simply about moderation. It is about infrastructure. Labels will need tools that can detect anomalies, attribute content accurately, and flag manipulation early. The industry must start treating data hygiene with the same seriousness as IP protection. AI-generated content is not inherently bad, but without systems to manage it, it can erode trust in streaming altogether.

Implementing robust detection systems and clear, industry-wide standards is essential for strengthening trust among artists, rights holders, and listeners.

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Sweden’s AI Licensing Model: A Glimpse Into the Future of Rights

While Spotify’s crackdown focuses on the risks of AI misuse, Sweden is showing what a structured, forward-looking approach can look like. In early September, STIM (Sweden’s rights organization) introduced a licensing model that allows AI developers to legally train on copyrighted songs while ensuring songwriters receive attribution and compensation. This new licensing model ensures that AI developers can train on licensed music while respecting creative rights and existing licensing agreements.

This model is one of the first attempts to bridge the gap between innovation and rights protection. Instead of fighting AI developers through lawsuits, STIM is creating a regulated environment where creativity and compensation can coexist. This approach addresses the evolving legal landscape and the need for a clear legal framework to govern AI usage and copyright laws in music creation. As AI trained on copyrighted songs is used to create music, new laws and updates to copyright law may be required to protect both human and AI-assisted creative works.

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Why it matters for labels:

• Legal clarity is coming. Labels that understand and engage with these licensing models early will shape how AI training and attribution work globally. The United States Copyright Office and other copyright offices are actively defining the copyright status of AI-generated works, clarifying when human involvement is required for copyright protection.
• New revenue streams are emerging. Licensing catalogs for AI training could become a major source of income if structured correctly.
• Strategic advantage is possible. Early adopters can position themselves as partners rather than obstacles, influencing how AI tools interact with their IP.

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Influur’s take:

This model is a hint of what is likely to happen worldwide. Labels should not wait for governments to dictate terms. They should begin exploring how their catalogs could be licensed for AI training in a way that protects artist rights while unlocking new value. This is about moving from a defensive to an offensive strategy. Labels should also work closely with industry partners to develop effective licensing models for AI training.

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Deepfakes, Authenticity, and the Battle for Trust

Beyond spam and licensing, another issue is escalating quickly. Deepfakes are becoming a central challenge. Sony has already removed tens of thousands of deepfake songs, and the debate over authenticity is intensifying. Vocal deepfakes and unauthorized use of artists' voices or copyrighted music present significant challenges for copyright protection and fair compensation.

AI makes it easy to mimic voices, styles, and entire performances. While this opens creative possibilities such as posthumous duets or fan-made remixes, it also raises ethical, legal, and reputational risks. Robust copyright protections are needed to protect creators from the misuse of AI-generated content. A single convincing deepfake can spread rapidly and damage trust between artists, audiences, and platforms.

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Why it matters for labels:

• Brand protection is becoming IP protection. Managing artist likeness is now as important as managing their catalog.
• Contracts must evolve. Labels need to address the use of AI voices, likeness rights, and derivative works explicitly.
• Audiences expect transparency. Listeners are becoming more aware of synthetic content, and trust will depend on clear labeling and ethical use. It's important to use AI responsibly and disclose AI involvement in music creation to maintain audience trust.

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Influur’s take:

Authenticity is not disappearing. It is being redefined. Labels that navigate this shift transparently will strengthen artist relationships and audience loyalty. This is not only a legal issue. It is also a cultural one.

Adopting an industry standard for labeling AI-generated content can help maintain transparency and trust.

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Sora 2 and the Next Wave of Social Music

Sora 2 is OpenAI’s new generative video platform that also functions as a short-form social app. Leveraging generative AI tools and AI music generators, Sora 2 enables users to produce new forms of AI art and AI generated works, significantly impacting the music business worldwide. Users can generate fully synthetic videos by simply describing a scene, then share and interact with this content in a feed that looks and feels similar to TikTok. The platform is currently invite-only, but it has already captured massive attention within the creator and music industries.

Billboard has described Sora 2 as a potential disruptive force in both social media and music. Unlike existing platforms that rely on remixing, Sora 2 allows creators to generate entirely new audio-visual experiences on demand. The AI output from these systems can be combined with human creativity to produce a unique final product. This shift could redefine how music is promoted, how fan communities form, and how artists show up in digital spaces.

Jake Paul has emerged as one of the platform’s most visible early adopters. In his own words, there is “a method to the madness.” He announced that he is a proud OpenAI investor, has been advising the Sora team, and became the first celebrity to opt into the NIL cameo feature. In just six days, AI-generated videos using his likeness accumulated more than one billion views. AI companies and AI entities are at the forefront of developing AI technology that is reshaping how AI generated music and AI music are created and distributed. His involvement has flooded social platforms with fictionalized, hyper-real AI versions of himself, creating both viral moments and new questions about identity and control. As AI generated music is produced through advanced AI systems analyzing vast datasets, the implications for the global music business include evolving copyright laws, new creative workflows, and challenges to traditional notions of authorship and ownership.

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Why it matters for labels:

• Distribution channels are shifting again. If Sora 2 gains traction, music promotion may move toward fully synthetic ecosystems.
• New creative formats will emerge. Artists and labels will need to understand how to produce for AI-native spaces where visuals and sound are generated together. The Recording Academy has stated that for AI-assisted works to be eligible for awards like the GRAMMYs, substantial human involvement is required, making it important for creators to consider recognition criteria as they adopt new technologies.
• Digital likeness management will become critical. Jake Paul’s example shows how fast synthetic identity can scale when paired with the right platform.

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Influur’s take:

Sora 2 is not a niche experiment. It reflects a major shift in how music, creators, and audiences may interact online. The platform is growing at a very fast pace. It surpassed one million downloads in just a few days and climbed to the top of the U.S. App Store rankings. Even with this early momentum, it is too soon to say whether it will become the dominant AI social platform. New platforms are emerging constantly, and the landscape is changing rapidly. Jake Paul’s involvement gives Sora 2 additional weight. Labels, artists and creators that start learning how to navigate and influence this type of environment now may gain a meaningful early advantage.

To maintain this advantage, it is essential for labels and artists to stay informed about new platforms and technological developments.

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The Pros and Cons of AI Generated Music in the Music Industry Right Now

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The Pros:

• Speed and scale are unmatched. AI accelerates creation and distribution, enabling artists and labels to experiment faster.
• New revenue models are opening up. Licensing for AI training and hybrid collaborations can create new opportunities, especially when prioritizing the use of licensed music. Artists are encouraged to use AI responsibly, ensuring transparency and compliance with industry standards.
• Creativity is expanding. AI allows new formats, virtual performances, and fan engagement models.

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The Cons:

• Spam and quality dilution are major concerns. Platforms are struggling to manage volume and protect artist visibility.
• Legal gray zones are growing. Rights, attribution, and compensation models are still unsettled, and there are increasing legal concerns regarding copyright issues, proper attribution, and fair compensation for AI-generated music.
• Authenticity is at risk. Deepfakes and synthetic content can undermine trust if unmanaged.

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Influur’s take:

The balance between innovation and integrity will define the next decade of music. Labels that build infrastructure, embrace licensing frameworks, and lead cultural conversations will thrive. Those that stay reactive risk losing both relevance and control.

As the industry evolves, it is essential to establish robust frameworks that protect creators and ensure their rights and livelihoods are safeguarded amidst technological change.

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Looking Ahead: Strategic Moves for Labels

1. Invest in detection and attribution tools. AI can help spot anomalies, flag deepfakes, and maintain catalog integrity.
2. Engage with licensing models early. Shape the rules instead of waiting for them to be written.
3. Educate artists and teams. Authenticity strategies should be proactive and transparent, and education and support should also extend to independent artists navigating AI in music.
4. Experiment with new platforms. Early presence on AI-native platforms like Sora 2 can set the tone for how music lives there.
5. Build hybrid teams. Combine creative talent with data intelligence to navigate this new landscape.

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Influur’s take:

Labels need sharper visibility and faster intelligence to keep up with the pace of change. That is exactly what we are working on with Influur Pulse, our upcoming platform built to give labels the cultural radar they will need to lead the next era of music marketing.

The Road Ahead

AI is reshaping how music is created, distributed, and experienced. As more works created with AI enter the market, there is a growing need for clear frameworks to address the legal status and copyright ownership of these creations. The pace of change is fast, and labels that treat AI as a strategic priority rather than a passing trend will be better positioned to adapt. As AI output becomes more prevalent, industry standards will be needed to ensure both quality and compliance. This moment requires clear frameworks, smarter tools, and informed decision making. Those who build the right infrastructure now will set the standard for how creativity and technology work together in the years ahead.

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FAQs

What is the impact of AI on the music industry today?

AI is reshaping how music is created, distributed, and experienced, introducing both opportunities for innovation and challenges like spam, copyright issues, and authenticity concerns.

Why did Spotify remove 75 million tracks recently?

Spotify removed these tracks because they were identified as AI-generated spam, often low-quality loops uploaded in bulk to manipulate streaming royalties, harming legitimate artists and the music ecosystem.

What is Sweden’s approach to AI music licensing?

Sweden’s STIM introduced a licensing model allowing AI developers to train on copyrighted songs legally, ensuring songwriters receive attribution and compensation, setting a precedent for global rights protection.

How do deepfakes affect artists and the industry?

Deepfakes, especially vocal impersonations, pose risks to artist identity, copyright protection, and audience trust, requiring robust legal and ethical frameworks to manage synthetic content responsibly.

What is Sora 2, and why does it matter?

Sora 2 is OpenAI’s generative video platform combining AI-generated audio and visuals, potentially transforming music promotion and fan engagement in AI-native digital spaces.

What are the main pros and cons of AI-generated music?

Pros include faster creation, new revenue models, and expanded creativity. Cons involve spam, legal uncertainties, and risks to authenticity and artist compensation.

What strategic actions should labels take regarding AI in music?

Labels should invest in detection tools, engage early with licensing models, educate artists, experiment with AI platforms, and build teams combining creative and data expertise.

How is copyright law evolving with AI-generated music?

Legal frameworks are developing to clarify human authorship requirements, licensing for AI training, and ownership of AI-assisted works, with ongoing debates about accountability and protection.

What role does human involvement play in AI music creation?

Human creativity and decision-making remain essential for copyright protection and artistic quality, with AI serving as a tool to enhance rather than replace human artists.

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