Artificial intelligence is evolving rapidly, and startups are seizing the opportunity to build proprietary models—language models, image recognition models, multimodal systems, and more. But amid this technical gold rush, one foundational issue is too often overlooked: intellectual property rights clearance. Whether you’re sourcing training data, fine-tuning a foundation model, or building from scratch, ignoring IP risks can derail your company—or worse, invite business or IP litigation. As an AI intellectual property lawyer, we help technology companies in Los Angeles and nationwide avoid costly missteps through strategic legal planning. Here’s what developers and founders need to know when training AI systems in 2025 and beyond.
1. Understanding IP Risks in AI Training Data
The backbone of any machine learning system is data—and much of it may be copyrighted or protected by other IP rights. Developers often assume that scraping publicly available data or using open-source datasets is risk-free. It’s not.
Common sources of infringement:
- Web-crawled content: Even if something is public, it’s not necessarily public domain.
- Copyrighted text or imagery: Used without permission, this can trigger claims under the Copyright Act.
- Logos and trademarks in image datasets: These create exposure under the Lanham Act.
- Personal data and biometric material: This opens the door to privacy and right-of-publicity lawsuits.
Data rights clearance is the first legal gate you need to pass.
2. How an AI Intellectual Property Lawyer Assesses Data Sets
Legal review of your datasets is not optional—it’s essential. Here’s how an AI IP lawyer can help:
- Audit your dataset sources: Are they scraped, licensed, public domain, or open source?
- Review dataset terms of use: Many platforms prohibit commercial re-use or training AI.
- Screen for trademark or brand misuse: Especially in visual datasets.
- Advise on fair use claims: Courts have yet to establish clear rules here—so don’t assume you’re protected.
- Evaluate third-party data vendors: Even “licensed” data may come with hidden restrictions or indemnity gaps.
Without this legal vetting, your model could be trained on a minefield of legal claims.
3. Legal Options for IP-Clean Training Data
The good news is there are IP-compliant paths forward. Here are legally sound options to consider:
A. Use Licensed Data
Obtain datasets that are explicitly licensed for AI training. Negotiate terms carefully—make sure your license includes rights to:
- Train commercial models
- Reuse and redistribute outputs
- Avoid downstream liability
B. Use Public Domain and Government Datasets
Look to sources like:
- Library of Congress collections
- NOAA satellite imagery
- Government archives Ensure you confirm their public domain status.
C. Commission Original Content
Hire creators to build custom image sets, voice recordings, or textual content. This gives you full ownership.
D. Apply Data Anonymization and Transformation
In some cases, legally risky data can be transformed to strip out IP-sensitive elements, making them safer for use.
Working with an AI intellectual property lawyer during dataset acquisition is essential to navigating these options effectively.
4. Traps to Avoid in Language Model Development
Training a large language model (LLM) involves more than just legal data sourcing. The model’s behavior—what it says, how it represents others, and how its outputs are used—can also create liability.
Watch out for:
- Defamatory model outputs
- Trademark confusion in responses
- Reproduction of copyrighted text verbatim
- Inclusion of false or misleading factual claims
Also, if your model is fine-tuning on customer data, ensure you have proper consent and terms of use in place. This is where privacy law and contract law intersect with IP.
A skilled legal team will help you set up guardrails—from the data license stage to the commercial use stage.
5. Protecting Your AI Model as Intellectual Property
5. Protecting Your AI Model as Intellectual PropertyOnce your model is trained, your legal risk doesn’t end. You now have proprietary software and model weights to protect. That includes:
A. Trade Secret Protection
- Keep training methods, data selection, and parameters confidential
- Use NDAs with vendors, employees, and contractors
- Build technical access controls
B. Copyright Protection
- While raw model weights may not be copyrightable yet, your training code, data labeling systems, and model architecture likely are
- Register copyrights where eligible
C. Patent Protection
- Consider filing for a utility patent if your model introduces novel architecture, training methods, or inference applications
D. Trademark Protection
- If you’re branding your model or platform (e.g., “LexiBot” or “ImageIQ”), secure federal trademark rights early
As your AI intellectual property lawyer, we develop IP strategies that scale with your model—from R&D to licensing and beyond.
6. Regulatory Watch: Legal Developments to Track in 2025
AI regulation is coming. Already, courts and lawmakers are grappling with AI’s legal impact. Key developments include:
- Pending lawsuits against OpenAI and Stability AI over training on copyrighted content
- State-level biometric privacy laws (e.g., Illinois’ BIPA)
- FTC and EU investigations into AI transparency and data use
- DOJ statements on AI anti-competition and collusion in training consortia
The legal landscape is volatile. Work with a law firm that understands the regulatory terrain—and can help you future-proof your IP and data strategy.
7. Legal Clearance Is Not Optional—It’s Your Competitive Edge
In the race to build market-dominating AI, legal clearance is not just about avoiding lawsuits—it’s about protecting your investment. A legally clean model is easier to license, partner with, insure, and sell. It enhances your valuation and investor appeal.
If you’re building AI without involving legal counsel, you’re building on sand.
Final Thoughts from an AI Intellectual Property Lawyer
The key takeaway: Don’t train first and ask questions later.
Work with a seasoned AI intellectual property lawyer before you collect your first image or tokenize your first prompt. From dataset licensing to model protection and commercialization, L.A. Tech and Media Law Firm is here to guide AI founders every step of the way.
David Nima Sharifi, Esq., founder of the firm, is a nationally recognized IP and technology attorney with decades of experience in M&A transactions, startup structuring, and high-stakes intellectual property protection, focused on digital assets and tech innovation. Featured in the Wall Street Journal and recognized among the Top 30 New Media and E-Commerce Attorneys by the Los Angeles Business Journal, David regularly advises founders, investors, and acquirers on the legal infrastructure of innovation.
Schedule your confidential consultation now by visiting L.A. Tech and Media Law Firm or using our secure contact form.
