Startups building a platform on ChatGPT or another large language model through an API must address several legal issues before launch: compliance with the model provider’s terms and usage policies, ownership and protection of what they build, privacy obligations for user data sent to the model, terms of service that allocate risk with users, potential liability for AI output, and AI-specific rules such as chatbot disclosure. Getting these right early is much easier than fixing them after customers sign up.
Picture a two-founder company that builds a customer support assistant on a commercial model API and starts selling to small businesses. Within months it is handling customer data for dozens of companies, its name includes “GPT,” and its marketing says the assistant “never makes mistakes.” Each of those facts creates a legal issue. Here is what to consider.
1. Follow the Model Provider’s Terms
Your platform depends on the provider’s API terms, usage policies and brand guidelines, which can change. Review them for:
- Prohibited uses. Providers restrict certain uses, such as some high-risk decisions about individuals, impersonation and generating unlawful content. You may be required to pass these restrictions on to your own users.
- Data handling. Confirm whether the provider retains API inputs, for how long, and whether they are used for model training. Business API terms often differ from consumer product terms.
- Output ownership and indemnities. Some providers offer IP indemnities for certain business customers, subject to conditions. Know what is covered and what is not.
- Branding. Provider brand guidelines may limit using marks like “GPT” or “ChatGPT” in product names, domains or logos.
- Dependency risk. Price changes, rate limits, model deprecations and suspension rights can affect your business. Consider whether your architecture should support more than one model.
2. Protect What You Build
Your value is likely in the application layer: your code, prompts and workflows, proprietary data, integrations and brand.
- Confirm that founders, employees and contractors have assigned their work to the company in writing.
- Treat system prompts, fine-tuning data and evaluation sets as trade secrets, with access controls and confidentiality agreements.
- Choose a distinctive brand you can register, rather than one built around another company’s mark.
- Remember that purely AI-generated content is not protected by copyright under current U.S. law, so human contribution matters for content you want to own.
See our discussion of intellectual property for startups.
3. Handle User Data Lawfully
Every prompt a user types may contain personal or confidential information, and your platform sends it to a third party.
- Privacy notices. California law requires a privacy policy for online services that collect personal information from California residents. If the CCPA applies, you must also honor consumer rights requests and limit how data is used and shared.
- Vendor terms. Make sure your agreement with the model provider includes appropriate data processing and service provider terms.
- Sensitive data. Health, financial, biometric and children’s data trigger additional rules. Many model providers do not permit use by children under 13, and COPPA applies to services directed to children.
- Enterprise customers. Business customers will ask for data processing agreements, security commitments and assurances that their data will not train models.
Our post on cybersecurity laws for AI startups covers security duties and breach notification.
4. Write Terms of Service That Fit an AI Product
Your user terms should address issues specific to generative AI:
- Acceptable use rules consistent with the provider’s policies.
- Clear statements that output may be inaccurate and should be reviewed, especially for important decisions.
- Who owns inputs and outputs, and what license you need to operate the service.
- Limitations of liability and warranty disclaimers, drafted to be enforceable under California law and presented so users actually agree to them.
- Subscription and automatic renewal terms that meet California’s disclosure and cancellation requirements.
5. Manage Liability for AI Output
Large language models can produce confident but wrong answers. If your platform gives customers inaccurate information about prices or policies, generates defamatory statements, or gives advice in regulated areas such as medicine, law or finance, your company may face claims. Courts have not settled whether existing protections for online platforms cover AI-generated content. Practical safeguards include limiting the assistant to defined tasks, grounding answers in approved sources, adding human review for high-stakes output, and avoiding marketing claims such as “always accurate” that you cannot support.
6. Track AI-Specific Rules
AI regulation is developing quickly. Relevant rules may include:
- California’s bot disclosure law, which prohibits using an undisclosed bot to mislead people about its artificial identity to drive a sale.
- Newer California laws addressing specific uses, such as companion chatbots, AI in employment decisions and generative AI transparency.
- Federal Trade Commission enforcement against deceptive AI claims.
- The EU AI Act, including transparency obligations for chatbots, if you serve users in Europe.
Our post on regulatory compliance for AI-based products covers these in more detail.
7. Get Commercial Contracts in Order
As you sell to businesses, you will negotiate customer agreements, data processing agreements, service level commitments and indemnities. Keep promises consistent with what your model provider promises you; otherwise you may owe customers more than you can recover upstream.
The Takeaway
Building on ChatGPT or another model can get a product to market quickly, but the legal responsibilities stay with your company. Review the provider’s terms, secure your IP, handle user data carefully, write AI-appropriate user terms and build safeguards against harmful output. A focused legal review before launch is usually far less costly than a dispute afterward.
Frequently Asked Questions
Can I use “GPT” or “ChatGPT” in my product name?
Using another company’s trademark in your product name creates risk. OpenAI’s brand guidelines restrict how developers may refer to its models and marks, and a name that suggests your product is made or endorsed by OpenAI could lead to a trademark dispute. A distinctive name of your own, with an accurate statement such as “built on” a named model where permitted, is the safer approach.
Who owns the output generated through the OpenAI API?
Major model providers’ business terms generally assign their rights in outputs to the customer, subject to the provider’s terms and policies. That does not mean the output is protected by copyright, because U.S. law requires human authorship, and the output may still be subject to third-party rights. Check the current terms for the specific service you use.
Do I need a privacy policy for a ChatGPT-based app?
Yes, in most cases. California law requires commercial websites and online services that collect personally identifiable information from California residents to post a privacy policy, and the CCPA adds detailed disclosure requirements for covered businesses. Your policy should explain that user inputs are processed by third-party AI providers.
Am I liable for what my chatbot says?
You may be. A company can be responsible for statements its chatbot makes to customers, and inaccurate or harmful output can lead to consumer protection, defamation, negligence or contract claims. Whether existing legal protections for online platforms apply to AI-generated content is unsettled, so careful design, disclaimers and human review in high-risk areas matter.
How Sutter Law Can Help
We advise AI startups on platform terms, privacy compliance, IP ownership, commercial contracts and AI regulatory questions. Learn more about our AI startup legal services, or contact us for a free consultation.
This article is general information, not legal advice. Reading it does not create an attorney-client relationship.
