How Can Traditional Model Agencies Own the Rights to Their Models’ Digital Twins?
Fashion Technology
Jul 3, 2025
Explore the complexities of digital twin ownership in fashion, focusing on legal, ethical, and technical challenges faced by model agencies.
Owning the rights to digital twins is becoming critical for model agencies as AI reshapes the fashion industry. These AI-powered replicas of models offer new revenue opportunities but require agencies to address legal, ethical, and technical challenges. Here’s what you need to know:
Digital Twins Defined: These are advanced 3D replicas of models used for virtual fashion, reducing costs and increasing efficiency in design and marketing.
Legal Frameworks: Agencies must navigate intellectual property laws, secure consent from models, and comply with regulations like New York’s Fashion Workers Act, which mandates clear agreements for digital twin usage.
Contract Essentials: Agreements should specify ownership, usage rights, pay rates, and liability terms, ensuring clarity and protection for both models and agencies.
AI and IP Management: Leveraging AI-driven tools can streamline digital twin creation and management, while robust intellectual property protections safeguard these assets.
Ethical Practices: Transparency, fair compensation, and respecting model autonomy are key to maintaining trust and staying compliant with evolving regulations.
Agencies that prioritize clear contracts, strong IP strategies, and ethical use of digital twins will position themselves for success in the growing $35 billion market.
Digital Twins Done Right? H&M’s Smart AI Move | Eline van der Velden
U.S. Legal Requirements for Digital Twin Ownership
Owning digital twins in the United States involves navigating a complex web of intellectual property (IP) laws, state regulations, and new AI-focused legislation. These legal frameworks are essential for safeguarding assets and avoiding disputes.
Key U.S. Laws That Affect Digital Twin Ownership
Understanding how fashion items are protected under IP laws - such as design rights, copyright, and trademarks - is crucial for securing digital twin ownership. However, digital twins introduce challenges that extend beyond traditional IP frameworks.
One significant complication is the disconnect between physical and digital ownership. For instance, the digital version of a garment may belong to the software license holder - typically the 3D designer or their agency - rather than the original designer of the physical piece. This gap in ownership can create conflicts that agencies need to address early on.
Digital twins generate valuable data, designs, and algorithms that fall under various forms of IP protection, including:
Patents for innovative technological processes or methods
Trademarks for brand identifiers and virtual goods
Copyrights for original creative works
Design patents for the ornamental aspects of unique products
Copyright law has expanded to cover digital assets like software, 3D models, and multimedia creations. This means original, creative works in digital formats are protected. In 2022, many trademarks were registered specifically for virtual goods, reflecting the U.S. Patent and Trademark Office's (USPTO) acknowledgment of digital assets as protectable property. Agencies must register federal trademarks for virtual goods and services to establish clear ownership boundaries.
"The original designer risks losing the right to recreate their own design if they do not retain the IP when translating into 3D. In the rush to get there with digital fashion there is a risk that the original designer could lose out."
– Alison Cole, Senior Trade Mark Attorney at UDL Intellectual Property
Next, let’s explore how New York’s legal mandates impact digital replicas of models.
The Fashion Workers Act and Its Requirements
New York's Fashion Workers Act, effective June 19, 2025, has reshaped the rules for creating and using digital replicas of models. Agencies must now obtain "clear and conspicuous written consent" from models before their digital replicas are created or used. This consent must include:
The intended scope of digital replica usage
The specific purpose of the digital twin
The agreed pay rate for its use
The duration of the digital replica's usage
Additionally, any existing power of attorney agreements that allowed digital replica usage became invalid on the Act's effective date. Future agreements must include explicit, separate consent.
The financial stakes are high. Models must be paid according to the terms outlined in their agreements, and violations of the Act carry steep penalties - $3,000 for the first violation and $5,000 for subsequent violations. The Act also empowers models to file complaints with the New York State Department of Labor and pursue legal action to recover damages, attorney’s fees, and additional compensation.
These regulations set the stage for addressing copyright concerns in AI-driven creations.
Copyright Issues with AI-Generated Assets
AI-generated digital twins present unique copyright challenges. U.S. copyright law protects original works created by humans, but it does not extend to outputs that involve minimal AI assistance. To qualify for copyright protection, a work must be both authored by a human and demonstrate originality. For example, simply giving prompts to generative AI software is unlikely to meet the threshold for copyright registration.
However, AI can still play a role in creating copyrightable works. If a human author significantly edits or creatively arranges AI-generated outputs, the resulting work may qualify for protection. The U.S. Copyright Office requires applicants to disclose the extent of AI involvement when seeking copyright registration, ensuring transparency about the role AI played in the creative process.
Agencies also need to consider the complexities of training data and international obligations, which can influence the copyright status of AI-generated outputs. To secure copyright protection for digital twins, agencies must ensure that human creative input remains a central element in their creation and fully disclose AI involvement during the registration process.
The solution lies in using AI as a supportive tool while maintaining the human originality required for copyright protection. This approach not only ensures compliance with current laws but also strengthens the legal foundation for digital twin ownership.
How to Secure Digital Twin Rights Through Contracts
Contracts play a crucial role in protecting both agencies and models by outlining the terms for creating, using, and maintaining digital twins, while ensuring compliance with evolving regulations.
Key Contract Terms for Digital Twins
Digital twin agreements require more specific clauses than standard modeling contracts. These should define the scope of digital twin development, detailing asset data documentation, integration requirements, and simulation standards. The contract must outline how the digital twin will be created, maintained, and updated throughout its lifecycle.
Ownership and data usage rights are critical. Clear licensing and assignment clauses should specify who owns the digital twin and how its data can be used. These terms should cover the entire lifecycle of the digital twin, ensuring agencies can safeguard their investments.
Intellectual property provisions are another key element. These clauses should clarify who holds the rights to the digital twin and its components, ensuring all parties understand their roles.
Security and privacy clauses are essential for protecting sensitive data. These should address how data is collected, stored, and used, aligning with broader data protection laws.
Liability and indemnification sections are also vital. These should clearly define accountability for issues like software failures or data breaches. They should specify liability limits, insurance requirements, and indemnification responsibilities, ensuring all parties understand their obligations. Additionally, contracts should include measurable standards for accuracy and performance, along with testing protocols and integration guidelines.
Exclusive vs. Non-Exclusive Rights: Making the Right Choice
Choosing between exclusive and non-exclusive rights depends on the agency's goals and budget. Each option has distinct advantages and drawbacks:
Rights Type | Advantages | Disadvantages |
|---|---|---|
Exclusive Rights | Full control over digital twin usage; stronger brand protection; prevents competitor access | Higher costs; limited flexibility; greater financial commitment |
Non-Exclusive Rights | Lower initial investment; shared development costs; more flexibility | Less control; potential competitor access; reduced exclusivity |
Exclusive rights give agencies complete control, preventing competitors from using the same digital twin. While this option often comes with higher fees, it ensures maximum protection for the agency’s brand and investment. It’s ideal for high-profile campaigns or when exclusivity is a priority.
Non-exclusive rights, on the other hand, allow multiple parties to use the same digital twin. This reduces costs and can provide models with more earning opportunities. However, it requires careful coordination to avoid conflicts between users and ensure fair distribution of responsibilities and rewards.
Best Practices for Contract Negotiations
Negotiating digital twin contracts effectively ensures they are both legally sound and practical.
Transparency is key. Agencies should clearly explain to models how their digital twin will be used, what data will be collected, and how it might impact their career or reputation. Open communication builds trust and avoids misunderstandings.
Contracts must address AI-specific risks, such as data breaches, intellectual property infringements, and algorithmic bias. For example, they should include indemnities from generative AI solution providers to cover potential issues like privacy violations or confidentiality breaches.
Regulatory compliance is another critical area. Contracts should adhere to data protection laws and adapt to changes in legislation. For instance, California’s AI Transparency Act, effective in 2026, will require companies to disclose AI-generated content, with penalties for violations.
To ensure fairness, contracts should include measures to identify and mitigate biases in AI algorithms and training data. Agencies can implement data governance standards and conduct bias checks at key stages of the AI model lifecycle.
Dispute resolution mechanisms are also important. Contracts should specify governing laws, jurisdictions for resolving disputes, and conditions for termination, such as breaches or termination for convenience.
Finally, contracts should outline maintenance and support procedures. This includes updating the digital twin as the physical asset evolves, providing long-term support, and setting service-level agreements to ensure the twin remains accurate and functional.
"Existing legal authorities apply to the use of automated systems and innovative new technologies."
This statement from federal agencies highlights the need to align contracts with established legal frameworks while addressing the unique challenges posed by digital twin technology.
Managing Digital Twin IP and Technology
Once digital twin rights are secured through contracts, agencies need effective systems to manage these intricate digital assets.
How to Protect Digital Twins with IP Management
Protecting digital twins involves multiple layers of intellectual property (IP) safeguards. The visual aspects - like the model's look, clothing, and styling - can be protected using copyright and design patents. These elements are critical as they make the digital twin both recognizable and valuable. The underlying code and algorithms that drive the digital twin may also qualify for protection through copyright, trade secrets, or even utility patents, depending on their originality and technical design.
Data models and training datasets often hold immense strategic value, making trade secret protections essential. These datasets can provide a significant edge in the competitive landscape. Additionally, user interaction features such as dashboards, alerts, and control interfaces may be eligible for copyright or design patent coverage.
Since IP rights are territorial, agencies should consider a global filing strategy to ensure protection in all key markets where they operate or plan to expand. Acting promptly is crucial, as digital twins tend to evolve over time.
Agencies should treat digital twins as strategic assets by documenting development milestones, contributor agreements, and licensing history. Tools like watermarking, audit trails, and access controls can help prevent unauthorized use. Licensing management systems also play a vital role in safeguarding these assets. Additionally, educating employees on IP policies strengthens these measures.
Using AI-Powered Solutions for Digital Twin Management
With IP protections in place, agencies can take digital twin management to the next level by leveraging AI tools. The digital twin market is growing at an incredible pace, projected to jump from $10.3 billion in 2023 to $73.5 billion by 2032. This growth has spurred the development of AI-driven management solutions that simplify and enhance the handling of digital assets. For instance, BetterStudio offers a specialized platform for fashion agencies, featuring AI-powered photo generation, customizable models, and advanced tools to help scale content creation while maintaining control over assets.
Generative AI plays a key role by producing synthetic data to train digital twin models more efficiently, improving simulation accuracy in the process. AI algorithms can also fine-tune model parameters to enhance realism, boosting the effectiveness of fashion photography and marketing campaigns.
Real-world examples highlight the transformative potential of these technologies. Siemens, for example, has used AI-powered solutions to cut factory downtime by up to 30%. In healthcare, generative AI integrated with digital twins has reduced patient wait times by 25% through optimized operations. These same efficiencies can be translated to the fashion industry, offering agencies a competitive edge.
Selecting an AI Platform for Digital Twin Management
When it comes to choosing the right digital twin platform, agencies should focus on scalability, flexibility, and how well the platform integrates with their existing workflows. BetterStudio’s platform, designed specifically for fashion agencies, supports high volumes of digital assets while streamlining operations. The platform offers flexible pricing options, including a free Basic plan, a Pro plan at $35 per month, and a pay-as-you-go model, making it accessible for agencies of all sizes and growth stages.
To maximize success, agencies should ensure their AI models are trained with high-quality data and incorporate feedback loops for continuous improvement. Identifying high-impact use cases for generative AI - such as automating repetitive tasks or enhancing creative projects - can also deliver significant benefits.
For example, BMW has implemented a virtual factory using digital twins, achieving millions in production cost savings and enhancing quality control. Similarly, Siemens uses digital twins to monitor wind farms, enabling remote adjustments that have increased energy output by 20% while cutting maintenance costs. These examples demonstrate the potential for similar efficiencies in the fashion industry, paving the way for smarter and more cost-effective digital twin management.
Ethics and Future-Proofing Your Digital Twin Strategy
As digital twin technology evolves alongside the growing influencer market, agencies face a dual challenge: staying ahead in innovation while maintaining strong ethical standards. The key is to develop sustainable practices that protect both agency interests and model rights, all while navigating a regulatory environment that’s still taking shape.
Balancing Agency and Model Rights
The fast pace of technological progress makes it more important than ever to strike a balance between the rights of agencies and the rights of models. Ethical use of digital twins begins with obtaining clear and explicit consent from models, ensuring they fully understand how, where, and for how long their digital likeness will be used. Contracts should include safeguards for intellectual property (IP) and fair compensation models, such as royalty percentages, usage fees, or hybrid payment structures.
Inclusivity also plays a pivotal role. Digital representations should reflect a broad range of demographics, appealing to diverse audiences and promoting representation across campaigns. Respecting model autonomy is equally important. Models should have the flexibility to set boundaries on how their digital twins are used - perhaps agreeing to fashion-related campaigns but opting out of other product categories or brand endorsements.
Staying Current with Changing Regulations
The regulatory framework for digital twins is still in its infancy, especially for complex applications. This uncertainty presents both risks and opportunities. Agencies can mitigate risks by conducting regular compliance audits to ensure their practices align with emerging ethical standards and new regulations. These audits should cover areas like network security, data integrity, and access controls.
Keeping up with regulatory changes requires monitoring developments at federal, state, and international levels. For instance, the US Food and Drug Administration's 2019 proposal to regulate AI-based software as "medical devices" highlights how quickly new rules can arise. Cross-department collaboration - bringing together IT, legal, and compliance teams - can help identify potential issues early. On top of that, implementing cybersecurity measures like Multi-Factor Authentication (MFA), encryption, and continuous monitoring not only strengthens data protection but also builds public trust, especially as concerns over privacy and data ownership grow. Transparency should remain a guiding principle as regulations continue to evolve.
Building Trust Through Clear Practices
Transparency is essential when managing digital twins ethically. Brands should openly disclose when digital models are used in campaigns and explain the technology behind these representations. Conducting ethical impact assessments before deploying digital twins can help uncover potential risks tied to privacy, algorithmic bias, and societal implications.
Ethical Do's | Ethical Don'ts |
|---|---|
Protect data privacy and security | Ignore algorithmic biases |
Include diverse perspectives | Overlook societal effects |
Use explainable AI for clarity | Depend solely on automation |
Regularly review and update systems | Treat ethical issues as one-time fixes |
Adhere to ethical guidelines | Disregard compliance requirements |
Engaging a wide range of stakeholders - such as ethicists, technologists, and end-users - helps bring balanced viewpoints into the process. Providing ethical training for employees involved in digital twin initiatives fosters a culture of accountability, covering critical areas like privacy, transparency, and bias mitigation.
Conclusion: Your Next Steps with Digital Twins
The shift toward digital twins in fashion isn't a far-off concept - it's happening right now. For traditional model agencies, the time to act is now. Success hinges on combining legal compliance, strong intellectual property (IP) management, and ethical accountability.
Start by solidifying a legal foundation. Secure IP rights and ensure compliance with data privacy regulations like GDPR and CCPA. Keep in mind that legal frameworks are evolving, so staying informed is crucial.
Next, focus on managing IP effectively. Work with specialized legal experts and utilize licensing platforms to simplify copyright registration and tracking. Draft clear agreements that address IP usage, data privacy, liability, and compliance.
Once the legal and IP aspects are covered, turn your attention to ethical practices. Transparency is key to earning consumer trust, particularly in light of concerns about data privacy - 78% of consumers worry about privacy issues, and 57% believe AI poses a significant threat to it. Build trust by implementing strong data protection measures, creating transparent governance structures, and using explainable AI to help users understand how algorithms work.
On the technology front, leverage tools to scale digital twin production. Platforms like BetterStudio offer AI-driven solutions for creating visuals, managing custom model features, and coordinating influencer campaigns, making them essential for modernizing your approach.
Finally, make risk management a priority. Regularly assess potential vulnerabilities, establish clear data management policies, and enforce strong security measures such as encryption and controlled access. Acting swiftly and thoughtfully will help set the standard for the industry.
FAQs
What legal hurdles do model agencies face in owning the rights to digital twins, and how can they address them?
Model agencies face a range of legal hurdles when it comes to digital twins, particularly around intellectual property (IP) rights, data ownership, privacy, and liability. With laws surrounding digital twins still in flux, agencies need to tread carefully. For instance, using third-party IP or data in creating and managing digital twins can complicate ownership and licensing agreements, leaving room for disputes.
To navigate these complexities, agencies should prioritize well-drafted contracts that clearly outline who owns the digital twin, how it can be licensed, and the scope of its usage. Keeping up with regulatory updates and consulting legal professionals experienced in AI and digital representation are also key steps. These measures can help agencies safeguard their interests and stay prepared for the evolving legal landscape.
How can traditional model agencies ethically use AI-generated digital twins?
To ensure ethical use of AI-generated digital twins, model agencies should focus on transparency and consent. It's essential that models are fully briefed on how their digital likenesses will be utilized and give explicit approval before any AI-related processes begin.
Agencies must also prioritize strong data protection policies to secure models' personal information. Additionally, they should work to eliminate biases in AI systems to prevent any form of discrimination. Partnering with ethical oversight organizations and AI developers can help establish practices that are fair, transparent, and in line with industry expectations.
Taking these measures allows agencies to integrate AI responsibly while upholding the rights and dignity of their models.
What key terms should be included in contracts to establish rights and usage for digital twins in the fashion industry?
When creating contracts for digital twins in the fashion industry, it’s crucial to spell out ownership terms. Clearly define who owns the digital twin and its related data to avoid any confusion down the line. Alongside this, make sure to detail usage rights and restrictions - this includes specifying how the digital twin can be used, where it can appear, and whether any modifications are allowed.
Another key aspect is outlining the scope of rights granted. This might involve approval processes for new uses or adaptations. Don’t forget to address data protection and liability, as this can help prevent disputes over sensitive information. Lastly, include provisions for intellectual property rights to cover designs, algorithms, or any data linked to the digital twin. This ensures that the agency’s creative and business interests remain protected.
By covering these points, agencies can better handle the legal and ethical challenges tied to digital twins while safeguarding their models and overall operations.