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AI in Music and the Challenges: An Analytical Report on Authenticity and Intellectual Property

Executive Summary

The rapid advancement of artificial intelligence (AI) is redefining the landscape of music creation, introducing both innovative tools and complex challenges. One of the most pressing issues is the unauthorized generation and distribution of music attributed to deceased artists on prominent streaming platforms like Spotify. This practice not only infringes upon intellectual property rights but also raises profound ethical dilemmas related to artistic legacy, reputation, and the integrity of an artist’s posthumous work.

This report details the inadequacy of current legal frameworks to address content generated entirely by AI, the critical gaps in streaming platforms’ content moderation, and the intricate interplay between copyright, publicity rights, and moral rights. It explores ongoing legal battles initiated by major record labels and collection societies against AI developers for the unauthorized use of data for model training.

As a solution, a multifaceted approach is proposed, including legislative reforms, enhanced platform accountability mechanisms, and proactive strategies for artist estates to protect their intellectual property and artistic legacy in the evolving digital landscape.

1. Introduction: AI in Music and the Challenges The New Frontier of AI in Music and Its Disruptions

Artificial intelligence has established itself as a transformative force across various creative industries, including music production, composition, and performance. Its ability to automate complex tasks, generate new ideas, and even replicate artistic styles has been widely recognized. However, this technological innovation presents a significant duality, functioning both as a powerful tool for creativity and as a source of substantial disruptions, especially concerning intellectual property and artistic authenticity.

The core of the problem lies in the increasing capability of AI algorithms to mimic the distinct styles, voices, and compositional patterns of artists. This has led to the creation of “new” tracks that are subsequently uploaded to official artist pages on streaming platforms, often without any authorization from their estates or rights holders. This particular phenomenon blurs the lines of authorship and authenticity, raising fundamental questions about the provenance and legitimacy of digitally available music.

A notable incident that served as a catalyst for industry concern was the case of Blaze Foley, a country singer who passed away in 1989. His Spotify page displayed an AI-generated song titled “Together.”¹ Craig McDonald, who manages Foley’s catalog, quickly identified the track as an “AI schlock bot” and not an authentic work by the artist.¹ The presence of an AI-generated image, which did not resemble Foley, on the song’s page further underscored the deceptive nature of the upload.² This episode starkly illustrated the vulnerability of artistic legacies to AI misuse on prominent streaming platforms. The appearance of such content on an official artist page, accompanied by an AI-generated image, suggests a deliberate attempt at deception rather than merely an experimental upload. This directly attacks the authenticity of an artist’s catalog, especially for those who are deceased, whose creative output is finite. If fans can no longer trust the content on official pages, the platform’s credibility as a reliable archive of artistic works is compromised. This situation is not limited to a mere copyright infringement; it points to the potential for widespread digital forgery that can distort an artist’s historical record and legacy, influencing fan perception and academic analysis of their work. Thus, the long-term integrity of digital music platforms as custodians of cultural heritage is called into question.

2. Case Study AI in Music and the Challenges: Unauthorized AI Tracks on Deceased Artists’ Spotify Pages

The investigation into the presence of artificial intelligence-generated music on deceased artists’ Spotify pages revealed a troubling pattern. In addition to the case of Blaze Foley, whose song “Together” was identified as inauthentic by his estate manager, Craig McDonald ¹, other artists have also been affected. Guy Clark, another country singer who passed away in 2016, had an AI-generated song, “Happened To You,” uploaded to his page, also accompanied by an AI-generated image that did not resemble him.¹ A third AI-generated song, “With You,” attributed to Dan Berk, was found with the same “Syntax Error” copyright mark.¹ The consistent presence of this mark across all three tracks suggests a common origin and a systemic problem, rather than isolated incidents.¹

The analysis of how these tracks were uploaded and Spotify’s initial response reveals significant vulnerabilities. The track “Together” was uploaded via SoundOn, a distribution service owned by TikTok.² This highlights the crucial role that third-party distributors play in the propagation of such content. Spotify confirmed the track’s removal, citing a violation of its “Deceptive Content policy.”² A Spotify representative attributed the incident to failures by the third-party distributor, rather than official uploads from a record label or artist estate.²

Despite the removal, there is substantial criticism regarding the platforms’ existing safeguards and content moderation protocols. Craig McDonald expressed concern about Spotify’s apparent lack of a “security fix” for this type of fraud, stating that “the responsibility is all on Spotify” to rectify this practice.¹ Critics argue that this case highlights “significant weaknesses in Spotify’s vetting process for music uploads and its capacity to prevent fraudulent content.”² While Spotify generally allows the distribution of AI-generated music, provided the creator holds the copyrights and does not violate platform policies ³, the removal of Foley’s tracks based on its “Deceptive Content” policy ² suggests that the issue for Spotify is not

purely the AI origin of the music, but rather its misrepresentation as an authentic work by a deceased artist. This indicates a reactive measure, triggered after the content is identified as fraudulent, rather than a proactive filter. Such a reactive approach implies that platforms currently rely on rights holders and the public to flag unauthorized AI content. Given the scale of AI generation, this is not sustainable. There is a policy gap: Spotify’s general permission for AI-generated music ³ creates a loophole for malicious actors to upload deceptive content, falsely attributing it. The core problem is

unauthorized attribution and deception, not just AI generation itself.

The fact that the content was uploaded via SoundOn, a TikTok-owned distributor ², points to a systemic vulnerability. Streaming platforms frequently rely on a vast ecosystem of distributors, which makes it challenging to verify every piece of content at the point of upload. The “failure” is attributed to the distributor ², but ultimately, the platform hosts the content and bears the reputational risk. This underscores a critical choke point for fraudulent content. More stringent verification and authentication protocols are needed not only at the platform level but also upstream, at the distribution services. This may require new industry standards for content provenance and identity verification for uploads.

3. The Legal Landscape AI in Music and the Challenges: Copyright, Authorship, and AI-Generated Works

The U.S. Copyright Office (USCO) holds a clear stance on human authorship as a prerequisite for copyright protection. The USCO has officially reaffirmed that works generated entirely by AI cannot be copyrighted.⁴ This is a fundamental principle: human authorship is an essential requirement.⁵ The rationale for this stance is that “extending protection to material whose expressive elements are determined by a machine… would undermine, rather than further, the constitutional goals of copyright.”⁵

The discussion around “prompt engineering” has also been addressed by the USCO, which clarified that “prompt creation is not sufficient human interaction to be considered an original work.”⁴ The USCO argues that “prompts alone do not provide sufficient control” over the output, and “the fact that identical prompts can generate multiple different outputs further indicates a lack of human control.”⁵ Furthermore, “selection of a single output is not, by itself, a creative act.”⁵

The copyright implications for derivative works involving AI are more nuanced. While wholly AI-generated works are not copyrightable, a work that “combines human creativity with AI can be copyrighted, provided there is a ‘sufficient’ amount of human expression.”⁵ The USCO notes that “the use of AI tools to assist, rather than stand in for, human creativity does not affect the availability of copyright protection for the output.”⁵ In derivative works, such as a remix, only the “new, original aspects can be copyrighted by the person who created it.”⁵ If a human modifies AI-generated elements “in a sufficiently creative way,” those modifications can be copyrighted, but not the underlying AI-created elements.⁵

The legal landscape is further complicated by ongoing challenges and lawsuits against AI music generators for the unauthorized use of training data. The music industry views AI’s use of copyrighted materials, without permission or compensation, as a matter of significant concern.⁵ Rights holders have “launched numerous lawsuits against AI developers who they believe used their copyrighted materials without permission or payment.”⁵ Major U.S. record labels (Universal, Warner, Sony) have filed high-profile lawsuits against AI music creation platforms like Suno and Udio, alleging “unauthorized use of their music libraries to train the models.”⁵ Germany’s GEMA, representing 95,000 German composers, also filed a lawsuit against Suno Inc. in January 2025, accusing it of using its members’ works without consent and profiting from them.⁶ GEMA presented evidence of AI-generated songs closely mirroring iconic tracks such as “Daddy Cool” and “Forever Young.”⁶ AI companies, such as Suno and Udio, have claimed their output is “transformative” and protected by fair use, a claim that has “drawn sharp rebuke from music industry leaders.”⁶

The USCO unequivocally states that wholly AI-generated works cannot be copyrighted.⁴ Simultaneously, major record labels and collection societies are suing AI companies for using copyrighted material to train their models.⁵ This creates a paradox: AI output, while potentially infringing on existing works, cannot itself be protected. This legal vacuum fosters a “wild west” scenario where AI-generated content can proliferate freely without clear ownership, making it difficult to control its distribution or enforce any rights. This encourages the creation of “schlock bot” content ¹ because there are no inherent copyright protections for the AI-generated work itself, nor a clear accountability mechanism if the

input data was used without permission. This paradox fuels the unauthorized use of AI to mimic artists, as the resulting “new” work lacks inherent copyright protection, complicating enforcement for the original rights holders whose style or voice was imitated.

AI companies argue “transformative use” ⁶ to justify training on copyrighted material. This is a common defense in copyright law, suggesting a new work has sufficiently altered the original to create a new meaning or purpose. However, the music industry has a “sharp rebuke” to this argument ⁶, especially when AI outputs closely mirror originals, as evidenced by GEMA.⁶ The outcome of these lawsuits will set a critical legal precedent for the entire creative industry. If “transformative use” is broadly accepted for AI training, it could fundamentally devalue creative works, allowing their uncompensated use as training data. If rejected, it will force AI developers to license content, creating a new economic model for AI-generated music that respects creators’ rights. This legal battle is defining whether the economic foundation of human creativity will be eroded or adapted.

Table 1 below summarizes the key legal positions and rulings on AI music copyright.

Table 1: Key Legal Positions and Rulings on AI Music Copyright AI in Music and the Challenges

Entity/Source	Main Position/Ruling	Implication
US Copyright Office (USCO)	Human authorship is required; wholly AI-generated works are not copyrightable; “prompt engineering” is insufficient; derivative works require “sufficient” human creativity.	Establishes the fundamental principle that AI cannot be a copyright author, but allows protection for works with significant human contribution.
RIAA (Recording Industry Association of America)	Supports USCO’s stance on the necessity of human authorship.	Aligns with protecting human creators’ rights and seeks to prevent the devaluation of music.
Court Rulings (e.g., Thaler v. Perlmutter)	Uphold USCO’s position that works created solely by AI are not copyrightable.	Reinforces existing jurisprudence, solidifying the need for human intervention for copyright protection.
Major Labels (Universal, Warner, Sony)	Suing AI developers (Suno, Udio) for unauthorized use of copyrighted material for training.	Seek to establish a legal precedent against unlicensed use of works for AI training, defending the economic value of intellectual property.
GEMA (Germany)	Suing Suno Inc. for using members’ works without consent and profiting, presenting evidence of similarity.	Highlights global concern over fair remuneration and transparency in AI training, aiming to protect composers’ rights.
AI Companies (Suno, Udio)	Claim “transformative use” to justify training on copyrighted material.	Seek to legitimize their business model, which, if successful, could redefine the boundaries of fair use and compensation.

4. Ethical Imperatives: Protecting Posthumous Artists’ Rights and Legacy AI in Music and the Challenges

AI’s ability to replicate a musician’s voice raises fundamental questions about the nature of artistic identity. The central debate revolves around whether a musician’s voice “should be protected as a personal privacy right or treated as a commercial property right.”⁷ Those advocating for voice as a personal privacy right argue it is an “intimate and non-transferable aspect of their identity.”⁷ Unauthorized AI replication of an artist’s voice, under this view, constitutes a violation of their personal autonomy and dignity, emphasizing the need for consent.⁷ Conversely, proponents of the commercial property right argue that voice should be treated as a property right that can be licensed, inherited, or sold.⁷ They suggest AI can introduce an artist’s work to new audiences and preserve their legacy ⁷, citing examples like hologram performances of artists such as Tupac Shakur and Whitney Houston.⁷

The exploration of publicity rights and moral rights (droit moral) is crucial in the context of AI replication. Publicity rights focus on an “individual’s persona” and are highly relevant when AI mimics an artist’s unique vocal traits, arguably creating a derivative work that implicates these rights.⁷ Cases like George Carlin’s estate successfully obtaining an injunction against an AI-generated podcast ⁸, and Tupac Shakur’s estate threatening Drake for using an AI-generated Tupac voice ⁷, demonstrate the application of these rights. Moral rights, which allow artists to “make decisions related to the preservation and protection of their connection to their work” ⁸, vary across countries. While the U.S. has a limited version, they include the right of attribution and the right of integrity (the right to object to changes to the work that may harm reputation).⁸ Picasso’s estate, for instance, cited copyright and moral rights infringement against AI-generated replication.⁸

The impact of unauthorized AI creations on an artist’s reputation, legacy, and artistic integrity is significant. The unauthorized use of AI to mimic artists, especially deceased ones, poses a “risk to their reputations.”² Craig McDonald, manager of Blaze Foley’s estate, stated that “it’s harmful to Blaze’s standing that this happened.”² Ethical concerns arise when AI-generated works are created “without the artist’s input or contrary to their artistic vision.”⁷ The posthumous release of Mac Miller’s album

Circles, for example, was seen as respectful because it built upon material he had already developed, contrasting with unauthorized AI use.⁷ Vast archives of artists like Juice WRLD raise questions about “dilution of the artist’s legacy” through excessive posthumous releases.⁷

The critical role of consent is paramount, for both living and deceased artists, regarding the use of their likeness and voice. Consent is fundamental.⁷ For living artists, contracts should specify terms for digital replication. For deceased artists, estate plans should outline posthumous usage preferences.⁷ Current legislation is “insufficient to address contemporary technological challenges” ⁹, pointing to the need for reforms that recognize “the complexities of AI-generated creations and ensure appropriate protection for human creators and deceased artists’ heirs.”⁹

AI offers a form of “digital immortality” by replicating an artist’s style and voice.⁷ While proponents argue this can preserve legacy and introduce artists to new audiences ⁷, unauthorized and non-consensual use, as observed with Foley ¹, fundamentally undermines this possibility. It transforms a potential homage into a form of exploitation, where the artist’s identity is commodified without their agency or their heirs’ consent. This raises a critical question about who controls an artist’s digital afterlife. Without clear legal and ethical safeguards, the creative output of deceased artists becomes an open field for AI exploitation, potentially leading to a flood of inauthentic content that distorts their true artistic vision and legacy. This could result in a “tragedy of the commons” for artistic identity.

Current copyright law primarily protects compositions and sound recordings, often for a defined period after death.⁸ Publicity rights protect persona ⁷, and moral rights protect integrity.⁸ However, ⁹ explicitly states that “current legislation is insufficient to address contemporary technological challenges.” The Carlin and Tupac cases ⁷, which required specific legal actions (injunctions, threats of lawsuits) rather than a clear, pre-existing policy, underscore this inadequacy. The disparate nature of existing laws (copyright, publicity, moral rights) means there is no single comprehensive legal instrument to address the complex issue of AI replicating an artist’s entire persona (voice, style, image) without consent, especially posthumously. This calls for new, integrated legal frameworks, potentially a federal publicity law ⁷, to provide clarity and protection in the AI era. The current legal patchwork creates ambiguity and forces reactive, costly litigation.

5. Industry Response and Platform Accountability

The reactions from artists, estates, and music industry bodies to the rise of unauthorized AI music have been of profound concern. Craig McDonald, manager of Blaze Foley’s estate, expressed significant alarm over the “harm” to Foley’s reputation and Spotify’s apparent lack of a “security fix.”¹ The Recording Industry Association of America (RIAA) “applauds the U.S. Copyright Office for reaffirming the longstanding tenet of copyright: human authorship is required.”⁵ GEMA CEO Dr. Tobias Holzmüller emphasized that AI providers use works without consent and “profit financially from them,” which he states erodes the economic foundation of musicians.⁶ Industry stakeholders, including label owners and music executives, have called for “immediate platform improvements to safeguard artist legacies.”²

Evaluating streaming platforms’ responsibilities in content verification and intellectual property protection is crucial. The incident has sparked discussions about “significant weaknesses in Spotify’s vetting process for music uploads.”² Critics argue that “the responsibility is all on Spotify” for not having a security fix.¹ Spotify’s response attributed the incident to “failures by the third-party distributor” (SoundOn), rather than official uploads.² Spotify’s general policy “allows the distribution of AI-generated music, provided the creator holds the copyrights… and it doesn’t violate the platform’s content policies.”³ This highlights a distinction between AI-generated music in general and

unauthorized/deceptive AI-generated music.

There is a growing call for enhanced AI detection tools, stricter upload policies, and improved collaboration with rights holders. Market observers anticipate “further announcements regarding content policy updates and potential adoption of more robust AI detection tools.”² Industry experts note that the streaming sector may face “tighter oversight to protect artists—living and deceased—from identity misuse, with major platforms likely to implement stricter controls and enhanced collaboration with rights holders.”² Kai Welp of GEMA emphasized that “providers of generative AI must respect copyright law and remunerate authors for their creative work.”⁶

Spotify’s reactive removal of Foley’s track ² and its reliance on third-party distributors ² illustrate a “whack-a-mole” approach. As AI generation becomes easier and more widespread, manual flagging and removal will be insufficient to combat the volume of potentially infringing or deceptive content. This necessitates a fundamental shift from reactive moderation to proactive prevention. Platforms need to invest heavily in advanced AI detection technologies and implement more stringent upload authentication processes. Stricter vetting of uploaders is required, implementing tighter identity checks for third-party distributors and direct uploaders to prevent fraudulent attributions. Clearer and more transparent AI content policies must be developed, distinguishing between authorized and unauthorized uses, especially concerning deceased artists. Enhanced collaboration with rights holders is critical, establishing direct and efficient channels for rights holders to report and resolve unauthorized content, moving beyond reactive flagging systems. Finally, exploring technologies like blockchain to create immutable records of content origin and rights ownership can ensure transparency and authenticity.

The emergence of companies like Soundverse.ai ⁶, which explicitly promote “ethical AI training” by allowing uploads of what one owns and offering “fair compensation” ⁶, suggests a potential market-driven solution. This stands in stark contrast to the “uninhibited use” ⁶ of copyrighted material by others. As public and industry scrutiny intensifies, AI developers and platforms that prioritize ethical data sourcing, transparency, and fair compensation may gain a competitive advantage. This could lead to a bifurcated AI music industry: one operating in a legally ambiguous “grey zone” and another built on licensed, transparent, and rights-respecting models. Consumer and artist preference could drive the adoption of the latter, fostering a more sustainable and equitable AI ecosystem.

In conclusion, the central debate revolves around whether an artist’s voice is a “sacred element of personal identity or a commercial property right.”⁷ The goal must be to ensure that musicians, living or deceased, “have agency over how their voices are used and remembered.”⁷ The future demands a delicate balance between fostering technological innovation and safeguarding human creativity and intellectual property rights. This will require ongoing dialogue, adaptive legal frameworks, and collaborative industry efforts.

AI in Music and the Challenges will continue to shape the industry’s future.

6. Future Outlook and Recommendations

The current landscape of AI-generated music indicates anticipated regulatory scrutiny and the potential need for new legislative frameworks to address AI in creative works. The incident on Spotify “should prompt both regulatory scrutiny and internal reviews at Spotify.”² Current legislation is “insufficient to address contemporary technological challenges” ⁹, pointing to the need for reforms. Legislative intervention, possibly a “federal law of publicity,” may be necessary to address the unique challenges of AI-generated voices.⁷ The future of artistic control “requires more than a one-size-fits-all approach.”⁷

The inevitability of regulatory intervention and the call for harmonization are evident. Repeated calls for legislative intervention ⁷ and the anticipation of “regulatory scrutiny” ² indicate that platform self-regulation and the current legal patchwork are insufficient. The global nature of streaming and AI content suggests the need for international harmonization of laws, similar to existing copyright treaties, to prevent jurisdiction shopping by malicious actors. This points to a future where governments will play a more active role in shaping the AI music landscape. The challenge will be to craft legislation flexible enough to adapt to rapidly evolving technology while providing robust protection for creators. This could lead to a global standard for AI content provenance and rights management.

For artists, estates, and rights holders, proactive strategies are essential to protect their intellectual property and legacy in the AI era. Proactive consent mechanisms are crucial: artists should clearly document their wishes regarding the use of their voice and likeness, both during their lifetime and posthumously, ideally through estate planning.⁷ Digital asset management is vital, requiring estates to have robust strategies for managing digital rights and monitoring online platforms for unauthorized use. Furthermore, licensing and collaboration with ethical AI development models should be explored, such as those involving licensing and compensation for artists whose works are used for training (e.g., Soundverse.ai⁶).

For streaming platforms, implementing robust authentication, content moderation, and rights management systems is recommended. This includes investing in and deploying advanced AI detection technologies to identify AI-generated content at the point of upload. Stricter uploader verification is needed, implementing tighter identity checks for third-party distributors and direct uploaders to prevent fraudulent attributions. Clearer and more transparent AI content policies should be developed, distinguishing between authorized and unauthorized uses, especially concerning deceased artists. Enhanced collaboration with rights holders is paramount, establishing direct and efficient channels for rights holders to report and resolve unauthorized content, moving beyond reactive flagging systems. Finally, exploring technologies like blockchain to create immutable records of content origin and rights ownership can ensure transparency and authenticity.

The emergence of companies like Soundverse.ai ⁶, which explicitly promote “ethical AI training” by allowing uploads of what one owns and offering “fair compensation” ⁶, suggests a potential market-driven solution. This stands in stark contrast to the “uninhibited use” ⁶ of copyrighted material by others. As public and industry scrutiny intensifies, AI developers and platforms that prioritize ethical data sourcing, transparency, and fair compensation may gain a competitive advantage. This could lead to a bifurcated AI music industry: one operating in a legally ambiguous “grey zone” and another built on licensed, transparent, and rights-respecting models. Consumer and artist preference could drive the adoption of the latter, fostering a more sustainable and equitable AI ecosystem.

In conclusion, the central debate revolves around whether an artist’s voice is a “sacred element of personal identity or a commercial property right.”⁷ The goal must be to ensure that musicians, living or deceased, “have agency over how their voices are used and remembered.”⁷ The future demands a delicate balance between fostering technological innovation and safeguarding human creativity and intellectual property rights. This will require ongoing dialogue, adaptive legal frameworks, and collaborative industry efforts.

7. Conclusion AI in Music and the Challenges: The Realization of Limitless Potential

The investigation into the claim that harnessing GPU power can unlock “limitless music production potential” reveals a compelling and well-founded argument. The inherent parallel processing capabilities of GPUs offer a fundamental architectural advantage over traditional CPUs, enabling an “almost unbound level of processing” for the increasingly complex demands of modern audio.¹⁰ This shift is not merely an incremental improvement but a paradigm change, moving from sequential bottlenecks to parallel liberation.

As demonstrated by pioneering tools like Audio Modeling’s SWAM line, Vienna Power House, Anukari 3D Physics Synthesizer, and sonicLAB’s Protean, GPU acceleration is already delivering tangible benefits. These applications show how GPUs facilitate hyper-realistic physical modeling, efficient convolution, and the creation of entirely new categories of instruments driven by complex physical simulations and massive polyphony.¹⁰

The “limitless potential” is further underscored by the technology’s accessibility—requiring only modern, non-specialized GPUs ¹⁰—and the visionary projections for its future. This includes ultra-low latencies, advanced multi-channel spatial mixing, real-time AI integration, and scalable cloud processing.¹⁰ These advancements promise to remove current computational barriers, allowing producers to realize creative ideas that were previously impossible.

In essence, GPU audio processing is poised to redefine the landscape of music production. It empowers creators to explore new sonic frontiers, achieve unprecedented fidelity and complexity, and seamlessly integrate cutting-edge technologies like AI into their workflows. The era of being limited by processing power is rapidly drawing to a close, ushering in an exciting future where the only true limit is the music creator’s imagination.

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