The first front in the music industry’s war against AI isn’t in the studio or on streaming platforms. It’s in the courtroom. Major rights holders, led by the RIAA, have filed lawsuits against generative music platforms like Suno and Udio, accusing them of “willful copyright infringement at an almost unimaginable scale.” The claim is straightforward: these systems train on vast libraries of copyrighted music without permission, and the resulting AI-generated tracks compete directly with human works. But the foundation for this legal push is far less stable than it might appear.
At the heart of the battle is the U.S. doctrine of fair use, a complex and often ambiguous legal concept meant to strike a balance between creative freedom and the protection of original works. AI developers argue that training on existing songs is “transformative,” not copying, but learning patterns in much the same way a human artist absorbs influences over a lifetime. They frame it as teaching a machine the grammar of music, enabling it to create something new. Rights holders counter that the process consumes entire compositions and that the outputs, even if novel, risk saturating the market, reducing licensing opportunities, and eroding the commercial value of human-made music.
The courts themselves are far from unified. In Andy Warhol Foundation v. Goldsmith, the U.S. Supreme Court narrowed the scope of what counts as “transformative” use, bolstering the argument that AI-generated works may serve the same commercial purpose as the originals. Yet other rulings have taken the opposite view, describing the use of copyrighted material in AI training as “quintessentially transformative.” The U.S. Copyright Office has added nuance but little clarity, noting that transformativeness is “a matter of degree” and questioning whether the analogy between AI learning and human learning is as straightforward as some claim.
This patchwork of legal interpretations leaves no clear path forward. Even if the RIAA scores a courtroom victory, the reality is that open-source AI models and decentralized development make the technology nearly impossible to contain. Once released, these models can be shared, modified, and deployed by anyone, anywhere, operating beyond the practical reach of most legal remedies. It’s the same dynamic the industry faced with Napster: shutting down a single company doesn’t stop the spread of the underlying capability.
For musicians, this uncertainty is more than just an abstract legal puzzle; it’s deeply personal. Our songs aren’t just content; they’re fragments of our lives and identities. The instinct to protect them is natural. But the blunt instrument of litigation may not be capable of stopping a technology that is already in the wild and evolving at breakneck speed. History shows that the law can slow technological change but rarely reverses it. As with past innovations, from digital sampling to peer-to-peer file sharing, the eventual outcome may be adaptation, not prohibition.
In the broader story of AI and music, this legal labyrinth is just one of several forces shaping an inevitable future. The real question may not be whether AI music can be stopped, but how artists, industry, and technology will learn to coexist in a creative landscape that refuses to stand still.
The rise of generative AI is profoundly disrupting the global music industry, creating a complex and fragmented landscape across major streaming platforms. At its core, this conflict pits the AI industry's view of public data as a training resource against the music industry's principle of intellectual property as private, licensable assets.
Here's a brief overview of this rapidly evolving landscape:
Divergent Platform Strategies: Major streaming services (DSPs) like Spotify, Apple Music, YouTube Music, Amazon Music, and Tencent Music Entertainment (TME) have adopted vastly different approaches to AI music.
United Rightsholder Opposition: In contrast to fragmented platform strategies, major labels and performing rights organisations are presenting a unified, aggressive opposition. They are executing a coordinated legal and legislative strategy, reminiscent of their response to file-sharing, to force generative AI into a controlled, licensed framework. They argue that unlicensed ingestion of copyrighted works for AI training constitutes copyright infringement and reject the "fair use" defence.
Emerging Monetisation and Systemic Fraud: While AI-native artists have shown market viability, achieving significant listeners on Spotify, this success is overshadowed by AI's role as an accelerant for sophisticated streaming fraud, siphoning an estimated £1 billion or more annually from the industry's royalty pool. This creates a vicious cycle where market saturation from low-cost AI content and fraud diminish economic prospects for legitimate human artists.
Legal and Ethical Crux: Core legal debates revolve around whether AI-generated works meet the human authorship requirement for copyright, the application of "fair use" to AI training data, and the protection of an artist's voice and likeness through publicity rights. Ethically, concerns include the pervasive lack of transparency and consent in AI model training, potential bias, and the broader devaluation of human artistry due to economic displacement.
Ultimately, the current state of conflict is unsustainable. The future is projected to be defined by an inevitable synthesis, involving the development of new licensing models for AI training, novel royalty distribution frameworks, and the deployment of advanced technologies like blockchain for transparent rights management. Navigating this transition requires stakeholders to embrace both aggressive rights protection and proactive engagement in shaping the ethical and commercial standards of this new, algorithmically-driven music economy.
The Imoliver Deal: A New Beat for the Music Industry?
On July 24, 2025, the music world witnessed a landmark event: Hallwood Media, a traditional full-service record label, signed a comprehensive recording agreement with Imoliver. What makes this deal revolutionary? Imoliver is explicitly described as a "human creator" who crafts songs "using nothing but lyrics and AI tools" from the generative AI platform Suno. This isn't just a distribution deal for a viral track; it’s a full-spectrum partnership covering artist management, production, global distribution, and marketing, mirroring traditional artist development.
Who is Imoliver? The "AI Music Designer"Imoliver, identified as Oliver McCann, is lauded not for traditional musical prowess but for his "prompt engineering, curation, aesthetic guidance, and taste-making". His breakout single, "Stone," amassed over 3.2 million streams on Suno before the deal, showcasing his ability to consistently generate appealing music across diverse genres. The deal strategically rebrands him as a "music designer," shifting focus from the AI tool to his human skill and artistic vision.
Hallwood Media's Vision: Embracing DisruptionFounded by industry veteran Neil Jacobson (formerly of Geffen Records), Hallwood Media positions itself as an "independent artist accelerator label" keenly focused on the intersection of music, technology, and new asset classes. This deal is a calculated move, seeing the ability to effectively guide powerful AI tools as a "new, valuable, and acquirable asset class". It effectively inverts the traditional A&R model, allowing Hallwood to invest in market-tested creations with lower overhead, tapping into an efficient new talent pipeline.
Navigating the Legal LandscapeThe deal operates amidst a "legal maelstrom". U.S. copyright law insists on "human authorship," often deeming AI-generated output ineligible for copyright protection, potentially placing it in the public domain. However, the Hallwood-Imoliver deal leverages Suno's Terms of Service for paid users, which contractually grants full commercial use rights to the generated songs, even if copyright isn't guaranteed. This creates a "strategic exploitation of the gap between the ambiguities of public copyright law and the certainties of private contract law". The broader industry, including major labels, is simultaneously suing AI platforms like Suno for copyright infringement while also negotiating licensing deals, highlighting the complex and divided landscape.
Industry Reaction and Future ImplicationsThe deal has sharply divided the music industry. Proponents like Neil Jacobson see it as "expanding what's possible," while many established artists and industry leaders view generative AI with alarm, citing fears of "devaluation and theft" due to training on uncompensated copyrighted music. This development puts immense pressure on streaming services to develop new policies regarding AI-generated content, moving it from a backend moderation issue to a front-end policy challenge.
Ultimately, the Hallwood-Imoliver agreement is a prototype for new creative partnerships, foreshadowing a "complex hybridization" of human and machine in music creation. It elevates the human skills of curation, taste, and aesthetic direction, reshaping the music value chain and ushering in "the era of the 'music designer'".
Join us as we explore the heated debate surrounding artificial intelligence in creative domains, addressing the "not fair" sentiment and anxieties about AI's "genuine creative spark". We'll demonstrate how these debates are not new, but echo historical disruptions like photography challenging painting, synthesizers redefining music, and digital art tools like Photoshop being criticised as "cheating". In each instance, technology forced a redefinition of artistic skill, shifting focus from manual execution to conceptualisation, curation, and the intelligent application of new instruments.
While AI excels at algorithmic ingenuity and rapid iteration, it lacks subjective experience, emotions, and consciousness – qualities central to the human "creative spark". This means AI output reflects patterns from existing works, risking aesthetic stagnation. The "not fair" sentiment is also driven by economic anxieties (job displacement) and copyright concerns, as AI often trains on copyrighted material and purely AI-generated work is generally not copyrightable under current U.S. law without human contribution.
The podcast argues that AI functions as a powerful tool that augments, rather than replaces, human creativity. The future of art will involve sophisticated human-AI partnerships where human judgment, curation, and the ability to imbue art with meaning remain paramount. The value of human art will increasingly lie in its authenticity, emotional depth, and the unique connection it fosters. This era demands new skillsets like "prompt engineering" and "AI artistry," reinforcing that artistic expertise adapts and evolves, but the human element remains irreplaceable for art that truly resonates.
The music industry is at a turning point as generative AI reshapes how songs are created and monetized. By flooding streaming platforms with cheap, infinite music, AI exploits the “pro rata” royalty model—diluting payouts for human artists. Industry forecasts suggest creators could lose over €10 billion in revenue by 2028. Cases like “Velvet Sundown” highlight how AI bands achieve algorithmic success with no real-world presence. Meanwhile, listeners say they prefer human art, but blind tests reveal they can’t tell the difference. This podcast explores how AI blurs the line between art and product, challenging the future of music itself.
The Velvet Sundown is a mysterious music project on Spotify that rapidly amasses hundreds of thousands of streams in 2025 despite having no real-world presence. Many suspect it is AI-generated, pointing to red flags like non-existent band members with distinctive but unsearchable names, uncanny AI-generated imagery, and a “flowery, ChatGPT-style” artist bio that even includes a fabricated Billboard quote.
The music is generic, “country-tinged roots-rock” with repetitive motifs like “dust,” described as having the “veneer of a Suno creation.” Distributed through DistroKid, the project’s rapid rise is attributed to sophisticated algorithmic manipulation. Its 26 tracks are “smuggled” into numerous large, popular user-curated playlists—such as “Vietnam War Music” and “The O.C. Soundtrack”—where they appear alongside genuine classics despite having no thematic connection.
This “blitz of placements” exploits Spotify’s recommendation system, triggering features like Discover Weekly and greatly expanding The Velvet Sundown’s reach. The phenomenon sparks heated debate among listeners, many of whom feel deceived and call for clear labeling of AI-generated content.
The case raises serious questions for the music industry about transparency, algorithmic responsibility, the economic impact on human artists, and the meaning of authenticity in music. It also prompts competitors like Deezer to implement AI detection and labeling policies.
The disruptive impact of new technologies on the art world by drawing a parallel between 19th-century photography and 21st-century generative AI.
Apple Music's increasing integration of artificial intelligence (AI) and machine learning (ML) to enhance user experience and personalisation. It details officially confirmed features already in use or set for release, such as AI-generated curated playlists like the 'Favourites Mix' and 'New Music Mix', the Autoplay function which intelligently queues similar songs, and the 'Listen Now' tab for personalised recommendations. The document also highlights natural language search capabilities via Siri and in-app, Apple Music Sing for vocal isolation, and the upcoming AutoMix for seamless DJ-like transitions. Furthermore, the text discusses rumoured or speculative AI features, including on-demand AI playlist generation, the potential for an 'AI DJ' with commentary, and a more conversational Siri. Finally, the acquisition of AI Music hints at future adaptive and generative music possibilities, showcasing Apple's commitment to subtly infusing AI across its music services for a more intuitive and personalised experience.
Licensing Battles:
The core conflict centers on major labels—Universal, Warner, and Sony—suing AI companies like Suno and Udio for copyright infringement. As the legal dust begins to settle, the focus is shifting toward licensing negotiations. These discussions include terms around fees, royalties, equity stakes, content identification systems, and control over platform features.
Creator Concerns:
Songwriters, publishers, artists, and ethical AI companies have voiced frustration and concern, feeling sidelined by potential deals between the labels and the same companies they once accused of infringement. Key worries include whether creators will have any influence over these agreements, if they’ll receive fair compensation, and whether these deals will erode the industry’s stance on responsible AI use.
The Rise of AI Artists:
Technological advancements—such as Suno’s powerful Song Editor—and the emergence of dedicated AI entertainment firms are giving rise to autonomous virtual artists, like Timbaland’s TaTa and Stage Zero. This marks the beginning of a potential new genre or movement, dubbed “A-Pop,” which began gaining traction in 2023.
Explore the evolving world of AI-generated music in our latest episode. We break down a recent U.S. Copyright Office report that reveals why music created solely by AI isn’t eligible for copyright protection, while tracks that blend human creativity with AI can be. We dive into what this means for musicians, the broader impact on the music industry, and how future reviews of AI training practices might shift the legal landscape. Tune in for a clear, insightful look at the intersection of law, technology, and creativity.
In this episode, we dive into the rapidly evolving world of AI-powered music creation. From Spotify's embrace of AI tools to SoundCloud's innovative remixing and beat-generation features, we explore how major platforms are shaping the landscape of music technology. We'll discuss the ethical debates around copyright and artist compensation, the role of AI in augmenting human creativity, and the potential impact on traditional music production skills. Join us as we unpack the balance between technological innovation and artistic integrity, and consider what the future holds for AI in music.
In this episode, we explore the dynamic and controversial world of AI in music, drawing insights from whatsupinmusic.com. We cover the rise of platforms like Google's Orca, which evolved into Lyria after copyright hurdles, and innovations like Suno V4 and Jen's StyleFilter which bring unprecedented creativity to music-making. We'll discuss the ethical and legal challenges around copyrighted material and how platforms like YouTube's Dream Track and Jen are pushing for transparency and artist consent.
We also dive into the political landscape, examining how deregulation and global policy shifts could shape the future of AI in music, from potential innovation booms to fears of displacing human artists. Finally, we'll reflect on how artists and the industry can adapt, innovate, and thrive amidst these transformative changes.
For today's podcast, we're diving into the buzz around "Now and Then," the Beatles' new track that uses AI to bridge past and present—and it’s making history with two Grammy nominations. This marks the first time an AI-assisted song has been nominated. In the episode, we'll explore how AI was used to clean up old recordings of John Lennon, allowing them to be seamlessly combined with fresh recordings from Paul McCartney and Ringo Starr. We’ll also discuss what this means for the music industry: the possibilities AI could bring for collaborations with iconic voices from the past and the big question of how much AI will shape the future of music creation.
In this episode, we dive into the transformative role of artificial intelligence in the music industry. We explore Universal Music Group's partnership with Klay Vision, aimed at enhancing music creation tools for artists, and discuss Timbaland’s collaboration with Suno AI, which raises ethical questions around AI's use of artists' work. From boosting creativity to navigating copyright concerns, we uncover how AI is reshaping the music landscape.
In this episode, we explore the intersection of music production and artificial intelligence, spotlighting a groundbreaking collaboration between renowned music producer Timbaland and AI music company Suno. Together, they aim to revolutionize the industry by merging human creativity with AI innovation. But as AI’s role in art grows, so do ethical concerns. We also dive into the controversy surrounding AI’s use of artists' work without consent, with over 10,500 creators protesting the practice. Join us as we unpack the future of AI in music and the challenges of ensuring ethical standards in the creative world.
n this episode, we dive into the transformative impact of generative AI across various industries. We'll explore how AI is reshaping creative fields, from music and visual effects to e-commerce and influencer marketing. Discover the latest advancements in AI-powered tools like Meta’s MusicGen and Roli Airwave, and learn how Industrial Light & Magic is using AI to push the boundaries of virtual production and visual effects. We’ll also tackle the ethical concerns around AI, such as data privacy and biases, and discuss the growing role of AI in content creation, influencer marketing, and even Spotify's music video integration. Tune in for a deep dive into the future of AI-powered creativity!
In this episode, we explore the rising impact of Artificial Intelligence in the music industry. AI is now being used to generate original music, remix existing tracks, and even create entirely new genres. We'll discuss the exciting possibilities this technology brings, such as increased accessibility and innovative creative avenues for artists. However, we'll also delve into the concerns surrounding AI's role in music—including the potential loss of human creativity and authenticity, the displacement of musicians, and the risk of music becoming homogenized. Join us as we navigate the complex landscape of AI in music production, weighing its benefits against the challenges it presents.
Join us as we navigate the exciting intersection of human creativity and technological innovation. Whether you're an artist, a tech enthusiast, or a music lover, this episode offers valuable insights into the future of music. Tune in to discover how AI and music are harmonizing to create new possibilities in the industry.
Welcome to today's episode of our podcast, where we explore the cutting edge of artificial intelligence in the music industry. In this installment, we'll dive into the recent developments that are reshaping how music is created, shared, and experienced.
First up, we'll discuss the controversy surrounding Snoop Dogg's AI-generated music video. This groundbreaking project has ignited debates about the role of AI in music creation. Is artificial intelligence enhancing artistic expression, or is it blurring the lines of originality and authenticity?
Next, we'll examine TikTok's strategic shift away from its TikTok Music streaming service. We'll unpack what this means for the platform's future, especially its plans to focus on live performances, artist promotion, and new music licensing deals. How will these changes impact users, creators, and the broader music landscape?
Finally, we'll delve into the broader implications of AI as a tool in music creation. We'll explore how these advancements are increasing accessibility, offering personalized experiences, and opening up new opportunities for collaboration and monetization for artists and creators alike.
Join us as we navigate the exciting intersection of human creativity and technological innovation. Whether you're an artist, a tech enthusiast, or a music lover, this episode offers valuable insights into the future of music. Tune in to discover how AI and music are harmonizing to create new possibilities in the industry.
