Recognizing the impact on human artistry: As AI performers become more visible, meaningful discussions are emerging amongst creatives around how their craft, identities, and livelihoods can be protected. These concerns echo across the history of the entertainment industry and range from compensation and job loss to consent for the reuse of likenesses or vocals.
As we examine the financial and business considerations of AI performers, the goal is not to position them as a replacement for human artistry. Instead, we are acknowledging their presence, the economic value they are generating, and that responsible management is essential to follow through on making sure the creative output of human and AI performers alike are treated with fairness, transparency, and integrity.
Key Takeaways:
- AI-generated performers like Tilly Norwood and Xania Monet are creating scalable, IP-driven revenue streams that require equal or greater financial oversight as traditional talent.
- Ownership of intellectual property and entity structure directly determine how income is earned, classified, and taxed across jurisdictions.
- As AI talent operates globally, business management and proactive tax planning are critical to manage complexity, compliance, and long-term value.
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She can appear in a brand campaign, headline a digital short, and license her likeness across three continents — all at the same time, without ever stepping in front of a camera. She is Tilly Norwood, recognized as one of the first AI-generated actresses, and she represents something the entertainment industry is only beginning to reckon with: talent that is entirely artificial, yet capable of generating real economic value.
Tilly was created by Eline Van der Velden, a Netherlands-based creative entrepreneur who built her through AI production company Particle6 and talent studio Xicoia. Van der Velden’s vision positions Tilly not as a gimmick but as the face of what she calls a new “AI genre” of content — scripted digital experiences built entirely around AI performers.
Meanwhile, in music, artists like Xania Monet are staking out similar ground: AI-generated musicians with original catalogs, streaming revenue, and a growing fanbase who may never think to ask whether there’s a human behind the voice.
The rise of AI talent is no longer hypothetical, it is generating revenue today. With that comes tax obligations, contractual complexity, and the need for structural business management. The industry is new, but the financial and legal fundamentals are not.
The Business Model Behind the Digital Performer
AI talent is inherently built on intellectual property. Tilly Norwood exists because Eline Van der Velden conceived her as a new form of licensable, scalable creative IP. Xania Monet exists as a recording artist with an original catalog, streaming revenue, and sync licensing potential across television, film, and advertising. In both cases, the asset is not a person but a proprietary creative identity, shaping how revenue is generated and managed.
Content production and licensing sit at the center of that model. A digital actress can be “cast” in multiple productions simultaneously, her likeness governed by agreements that function not unlike traditional screen rights — except that the underlying asset is a piece of owned technology, not a human being. A song performed by an AI musician may generate royalties on Spotify today, appear in a television advertisement next quarter, and be sublicensed into a video game soundtrack the year after. The IP can scale in ways that are difficult for traditional talent models to replicate.
Brand endorsements and sponsored content layer on top of this foundation. Once a digital persona starts building an audience, brands may integrate that character in their marketing or storytelling efforts. These arrangements resemble traditional endorsement deals, but they introduce nuances around copyright, likeness rights, and who manages the character over time. For the creator or company behind the AI performer, these offer another possible income stream.
Opportunities surrounding AI talent do come with significant risks. Given the current lack of established guardrails under how AI performers are created and operate, there is significant uncertainty about ownership, boundaries on the usage of likenesses, and who controls them in the long-term — all of which represent material business risks. Licensing agreements that were once straightforward with human talent could be inherently more complex with AI talent as parties involved in the deal seek precision in the definitions of usage, updates, attribution, and more to avoid future conflicts as technology powering the AI performer changes over time.
IP Ownership Changes Everything
In the AI talent economy, the “talent” is a layered IP asset — combining creative vision, models, data, and contractual rights. Ownership across this stack directly shapes revenue flow and tax treatment. As we are just now seeing the emergence of AI performers, ownership considerations, including training data and likeness outputs, remain evolving and may be subject to ongoing legal and regulatory developments.
Consider royalties. When Xania Monet’s music generates streaming revenue, who receives the royalty payment? If Van der Velden’s company Particle6 holds the IP for Tilly’s likeness, how are licensing fees structured and reported? These are practical questions encountered in contracts, tax reporting, and, in some cases, litigation. The entity structure behind an AI talent determines how income is categorized (royalty income vs. service income vs. licensing fees carry meaningfully different tax treatment), how deductions are applied, and how the underlying intellectual property is valued for estate or transfer purposes.
Getting the entity structure right from the start — and revisiting it as the talent’s revenue profile evolves — is foundational business management work. It is also the kind of work that is easy to put off until the numbers get large enough to make errors expensive.
The International Dimension
AI talent is inherently borderless. A digital performer has no passport, no work visa, and no preference for domestic markets. Content featuring Tilly Norwood can be produced in the Netherlands, distributed on a U.S.-based platform, consumed by audiences in South Korea and Brazil, and generate licensing revenue that flows through a corporate entity registered in a third jurisdiction. Increasingly, this represents a common operating model for globally distributed digital content.
The tax implications are significant and multi-layered. Royalty income and licensing fees earned across multiple jurisdictions trigger withholding tax considerations in each country where income is sourced. Depending on treaty arrangements and the structure of the IP-holding entity, the effective tax burden can vary substantially. Transfer pricing rules — which govern how income is allocated between related entities in different countries — apply to AI talent companies just as they do to multinational corporations, because in effect, that is what a globally distributed AI talent operation is.
State and local tax compliance adds another layer. In the United States, digital content and licensing income may be subject to varying treatment across states, some of which have moved aggressively to tax remote or digital-sourced income. A business manager and tax team who understand both the international treaty landscape and the domestic state and local tax (SALT) environment are increasingly critical for sustained growth and compliance.
Same Industry, New Rules — With the Same Need for Management
AI talent is often framed as a technology story — a fascinating development in generative AI with implications for creative industries. It is that. But it is also, at its core, a talent story. Tilly Norwood and Xania Monet are talent. They have managers, revenue streams, IP portfolios, audience relationships, and brand equity.
The business infrastructure that human talent has relied upon for decades — business management, tax planning, contract negotiation, royalty accounting, entity structuring — does not become irrelevant because the talent is digital. In practice, complexity often increases. The IP questions are harder. The international exposure is greater. The entity structures are more consequential. And the pace of the market means that decisions made today about ownership, licensing, and revenue allocation will have compounding effects for years.
In a market moving this fast, the entertainers, agencies, and creative entrepreneurs entering the AI talent space are making long-term financial decisions in real time, often without the guidance they need. That is precisely the kind of environment where experienced business management and tax counsel make the difference. For media companies, agencies, and investors, the question is no longer whether AI talent will scale, but how to structure it correctly from the outset to avoid costly missteps.
How MGO Can Help
MGO’s Entertainment, Sports, and Media practice has deep experience advising talent, creators, managers, and media companies on the financial and tax complexities of a rapidly evolving industry. Our team includes tax professionals with experience in international tax, state and local tax, credits and incentives, and more — as well as experienced business managers who understand how entertainment revenue flows and how to structure it effectively.
Whether you are a creator building the next generation of AI talent, a manager advising clients who are entering this space, or an agency evaluating how AI performers fit into your existing roster, we can help you navigate the business and tax considerations that come with this emerging market. Contact our team today to discuss how we can support your AI talent strategy.