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Universal and Warner Music Close to Striking Landmark AI Licensing Deals

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Universal Music Group (UMG) and Warner Music Group (WMG) are reportedly on the verge of signing major artificial intelligence licensing agreements that could reshape how music is used and monetized in the AI era, according to a Financial Times report published Thursday.

Sources familiar with the discussions said that both music giants could finalize their deals within weeks, as they negotiate with a mix of AI start-ups and major tech companies.

Among the start-ups in talks are ElevenLabs, Stability AI, Suno, Udio, and Klay Vision. The labels are also in advanced discussions with industry heavyweights such as Alphabet’s Google and Spotify, according to the report.

Neither Universal, Warner, Google, nor Spotify immediately responded to Reuters’ requests for comment.

TOWARD A NEW MUSIC-AI BUSINESS MODEL

The potential deals represent a pivotal moment for the music industry, which has long battled unauthorized AI-generated content and the use of copyrighted works to train generative models. If completed, the agreements would establish a formal licensing framework allowing AI firms to access and use songs legally — for both music generation and AI model training.

Negotiations have reportedly focused on creating a payment system modeled after music streaming royalties, where every use or AI-generated playback of a song would trigger a micropayment to rights holders.

LEGAL AND ETHICAL PRESSURES ON AI FIRMS

The rise of generative AI has fueled a surge in lawsuits from artists and rights holders, accusing companies of using copyrighted material without consent or compensation. These potential licensing deals could help defuse legal tensions while providing a new revenue stream for record labels.

AI companies like ElevenLabs and Suno have been pushing the boundaries of voice synthesis and music generation, raising ethical questions about authorship and originality. By formalizing partnerships with major labels, these firms could legitimize AI-created music and ensure artists receive compensation.

A LANDMARK SHIFT FOR THE INDUSTRY

If finalized, these agreements would mark the first large-scale AI licensing model in the global music industry — a step that could influence how other creative sectors handle the intersection between AI and copyright.

Music industry observers say such deals could become a template for balancing innovation with intellectual property protection, ensuring that the creative ecosystem adapts rather than resists AI’s growing influence.

ElevenLabs Staff to Sell Shares at $6.6 Billion Valuation

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ElevenLabs, the fast-growing voice cloning AI startup, is allowing employees to sell shares at a $6.6 billion valuation, double its January 2024 value of $3.3 billion, according to Bloomberg News. The move highlights the ongoing competition among AI firms to retain top talent by offering stock liquidity.

The tender offer will enable staff who have worked at the company for at least a year to sell up to $100 million worth of shares, giving them an opportunity to cash out while allowing investors to boost stakes. Sequoia Capital and Iconiq are leading the deal, joined by Andreessen Horowitz and other backers.

Founded by Piotr Dabkowski (ex-Google) and Mati Staniszewski (ex-Palantir), ElevenLabs has seen explosive growth. Its headcount jumped from 77 employees to 331 in a year, while annualized recurring revenue surged from $100 million in October 2024 to $200 million in mid-2025. The company aims to hit $300 million by year-end.

The valuation leap puts ElevenLabs among the most valuable AI startups in the world. It comes as OpenAI also explores an employee stock sale that could value it at $500 billion, underscoring how AI’s growth is reshaping private markets.

ElevenLabs Launches Agent Transfer Feature for Seamless Data Sharing Between AI Agents

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ElevenLabs has unveiled a new enterprise-focused feature that enables seamless communication between artificial intelligence (AI) agents, introducing what they call the “Agent Transfer” feature. This feature is designed to allow one AI agent to pass a conversation on to another when certain conditions are met, ensuring a smooth handover of information. The key advantage of Agent Transfer is that it not only transfers the conversation to a new agent but also shares the history of the discussion, helping the new agent understand the context and continue the conversation seamlessly. This feature is particularly beneficial for businesses looking to create specialized AI agents with different areas of expertise, allowing them to collaborate effectively.

The announcement was made on X (formerly known as Twitter), where ElevenLabs introduced the feature as part of its broader Conversational AI toolkit. While Agent Transfer is currently available for enterprises, ElevenLabs has not clarified whether this feature will be offered as a standalone service or integrated into existing plans. The company has also provided developers with instructions on how to implement the feature through its support pages, making it accessible for businesses to integrate into their existing AI workflows.

As more companies incorporate AI agents into their operations, the challenge of avoiding data silos becomes increasingly important. Traditional AI systems often struggle with sharing data across different functions, leading to inefficiencies where information is trapped within one segment of the business. ElevenLabs’ approach with Agent Transfer seeks to address this issue by enabling AI agents to communicate directly with each other and share valuable data. This helps ensure that the right knowledge is accessible at the right time, enhancing the effectiveness of AI interactions.

The practical implications of Agent Transfer are significant. For example, if a customer service AI agent encounters a situation where it cannot adequately assist a user, the conversation can be transferred to a more specialized AI agent without requiring human intervention. The second agent receives the full conversation history, allowing it to pick up the discussion without the need for the user to repeat themselves. This not only improves the user experience but also boosts the overall efficiency of AI-driven customer service operations.