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The music industry's big three, Universal, Sony, and Warner, are pushing for stricter chart eligibility rules that could exclude songs primarily created by artificial intelligence.
The music industry is at a crossroads as it grapples with the rapid advancement of artificial intelligence (AI) in song creation. Major record labels, including Universal Music Group, Sony Music, and Warner Music Group, have proposed new rules to ensure that only "substantially human made" songs are eligible for international charts. This move is part of a broader effort to address concerns over data protection, ethical AI use, and the preservation of human creativity.
The proposal, which goes beyond a labeling initiative introduced by the Recording Industry Association of America (RIAA) and others, aims to create clear guidelines for what constitutes an AI-generated song and how it should be treated in the music industry. The RIAA's plan involves standardized labels to distinguish between AI-generated and human-created content, but the major labels' proposal takes a more stringent approach.
To qualify for international charts under the proposed rules, songs must meet specific criteria. They must be "substantially human made," which means that significant creative input must come from human artists rather than AI algorithms. Any AI service used in the creation of a song must adhere to its terms of service, and the model must have the right to use any data it was trained on. This requirement is designed to protect intellectual property and ensure fair use of existing music data.
The proposal also emphasizes transparency by requiring that songs be clearly labeled as AI-generated or AI-assisted. This labeling system aims to inform listeners and consumers about the role of AI in the creative process, promoting honesty and trust within the industry. However, the definition of "substantially human made" remains somewhat ambiguous, leaving room for interpretation and potential disputes.
For example, what percentage of a song must be created by humans to meet this criterion? How will the industry verify that a song meets these standards? These questions highlight the complexity of implementing such rules and the need for clear, enforceable guidelines.

The stakes are high for both the music industry and artists. AI-generated music has the potential to revolutionize how we create and consume music, but it also raises significant ethical and legal concerns. On one hand, AI can democratize music creation by providing tools that lower barriers to entry for aspiring musicians. On the other hand, there is a risk that AI could undermine the value of human creativity and artistic integrity.
For established artists, the fear is that AI-generated songs could flood the market, diluting the impact of their work and potentially leading to a loss of revenue. The major labels' proposal aims to strike a balance by promoting transparency and protecting the interests of human creators while allowing for the responsible use of AI technology.
The music industry's response to AI will have long-term consequences. If handled poorly, it could lead to a backlash against AI in creative fields, stifling innovation. Conversely, if managed well, it could set a precedent for ethical AI use that benefits both creators and consumers.
Ultimately, the proposed rules are a step toward ensuring that the music industry remains a space where human creativity is valued and protected, even as technology continues to evolve. As the debate around AI in music unfolds, it will be crucial for all stakeholders to engage in open dialogue and collaboration to find solutions that work for everyone.
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Original Sources
The major labels propose rules to keep AI slop off the charts
↗ https://www.theverge.com/ai-artificial-intelligence/973741/ai-music-major-record-labels-charts
About the author
Amara's entry point into AI was an epidemiology role at a London research hospital, where she spent five years studying how digital health tools reached — or conspicuously failed to reach — underserved communities. Watching early algorithmic systems in healthcare quietly entrench existing inequalities, she redirected her career toward the systemic consequences of AI at scale. She covers AI through an unflinching lens: who benefits, who bears the cost, and what evidence actually says versus what the press release claims. Her writing is calm and precise, but she doesn't mistake balance for neutrality.
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6 August 2026
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