Copyright law was not written with AI in mind, and that gap is expensive for founders who discover it too late.
Generative AI tools produce text, images, and code at a speed that makes it easy to publish before asking basic questions: who owns this? could this hurt someone? am I breaking a law I have never heard of? As of mid-2024, courts are actively answering those questions, and the answers are not always what businesses assumed.
This article covers the five legal questions every founder should resolve before AI-generated content becomes a material part of their product or marketing.
Who owns the copyright on AI-generated text and images?
The short answer, under current US law, is that no one does.
In February 2023, the US Copyright Office issued guidance stating that AI-generated content with no human authorship receives no copyright protection. The Office reinforced this in its March 2023 registration policy: only content with sufficient human creative control qualifies for registration. If a person types a prompt and accepts the AI output verbatim, the output is not copyrightable.
That matters for two reasons. If you cannot copyright your AI content, competitors can copy it without consequence. And if you publish AI content alongside human-written content without tracking which is which, you may inadvertently weaken copyright claims on your human-authored work.
The human authorship threshold is not clearly defined, but the Copyright Office has said that selecting, arranging, or modifying AI output can qualify. A founder who writes a detailed prompt, edits the result, selects among multiple outputs, and integrates it into a broader creative work has a stronger claim than someone who copies AI output directly. Courts in the EU are working through similar questions, with no settled answer yet.
Practical takeaway: track which content was written by humans and which was AI-generated. For content that matters to your brand, have a human edit it materially. For content where copyright ownership is commercially important, speak to an IP attorney before publishing.
How does training data create infringement exposure?
Large AI models learn by ingesting enormous amounts of existing text, images, and code. Some of that material was copyrighted. Whether that training process itself infringes copyright is one of the most contested legal questions in technology right now.
Several high-profile lawsuits filed in 2023 and 2024 make the stakes concrete. The New York Times sued OpenAI and Microsoft in December 2023, alleging that training on its articles without license or compensation infringes its copyright. Getty Images filed a similar suit against Stability AI in January 2023, claiming that 12 million copyrighted images were used to train the Stable Diffusion model without permission. Authors Guild members, including George R.R. Martin and John Grisham, filed a class action against OpenAI in September 2023.
None of these cases have reached final verdicts. The legal theory being tested, that training on copyrighted data infringes the copyright holder's reproduction rights, has not been definitively accepted or rejected by a federal court. But the volume of litigation means the risk is not theoretical.
As a founder, your exposure depends on how you use the output. If an AI tool generates marketing copy that closely resembles a specific copyrighted source because that source was in its training data, you could face an infringement claim even though you did not intentionally copy anything. The tool's vendor is the primary target in most suits, but downstream users are not always insulated.
Check whether the AI tools you use have indemnification clauses covering copyright claims. OpenAI, Adobe, and Microsoft have each announced some form of copyright indemnification for commercial customers as of 2024, though the scope varies and conditions apply. Read the terms before assuming you are covered.
Can I be liable if AI content contains defamatory statements?
Yes. Publishing defamatory content is a legal risk regardless of who or what generated it.
Defamation is a false statement of fact about a real, identifiable person that causes harm to their reputation. The fact that an AI produced the statement does not shift liability away from the publisher. Under US law, you are the publisher when you put content on your website or distribute it through your product, even if an AI wrote every word.
AI models hallucinate. That is the term the industry uses when a model generates confident, plausible-sounding text that is factually false. When that false text concerns a real person, the defamation exposure is real.
A widely cited 2023 incident involved ChatGPT fabricating a sexual harassment allegation against a law professor, complete with a fake Washington Post article as a citation. The professor, Jonathan Turley, discovered the fabrication when it appeared in research generated by the tool. No lawsuit resulted, but the scenario illustrates exactly how hallucinated content about real people can be published and distributed before anyone checks the facts.
The risk is higher for content that is automatically generated and published without human review: AI-written product descriptions that name competitors, summaries of public figures' statements, or any content where the AI is asked to write about specific real people or businesses.
Human review before publication is the most direct mitigation. For any AI content that mentions named individuals or organizations, a person should verify every factual claim before it goes live. The cost of review is low. The cost of a defamation claim is not.
What contract language should I add for AI-produced work?
Two contract relationships matter here: agreements with the AI vendors you use, and agreements with clients or contractors when AI-generated work changes hands.
On the vendor side, the most important clause to locate is the indemnification provision. As noted above, some AI providers have introduced IP indemnity programs, but these typically require you to use the tool through approved commercial APIs, not modify the output in ways that introduce additional third-party content, and report claims promptly. Review the specific terms for each tool you use.
On the client and contractor side, the legal uncertainty around AI content creates contract gaps that neither party has historically anticipated. The table below shows the clauses worth adding when AI-generated work is involved.
| Clause | What it covers | Why it matters |
|---|---|---|
| AI disclosure clause | Requires the contractor to disclose when deliverables are AI-generated | Prevents surprise and lets you apply appropriate review |
| Ownership acknowledgment | States that AI-generated elements carry no guaranteed copyright and ownership terms reflect that | Avoids disputes about who owns what after delivery |
| Accuracy warranty | Contractor warrants that AI-generated factual claims have been verified before delivery | Allocates defamation and misinformation risk to the party doing the generating |
| Indemnification for IP claims | Party using AI tools indemnifies the other for third-party copyright claims arising from AI output | Specifies who bears the cost if a training-data lawsuit implicates the work |
| Review obligation | Specifies that a human reviewed the AI output before delivery | Creates a paper trail showing due diligence |
If you are buying AI-generated content from a vendor or contractor, ask explicitly whether AI was used and request confirmation that a human reviewed it. If you are delivering AI-assisted work to a client, disclose it and keep records of your review process. The norm in 2024 is still inconsistent, but the direction of regulation in the EU and several US states is toward mandatory disclosure.
Do disclosure requirements apply to AI content on my site?
This is moving faster than most founders realize.
The EU AI Act, which received final approval in May 2024, requires that content generated by AI and designed to resemble authentic human content must be labeled as AI-generated. The Act takes effect in phases, with high-risk AI systems facing compliance obligations as early as mid-2025. Businesses operating in the EU or targeting EU customers are subject to these requirements.
In the US, there is no federal AI disclosure law yet, but sector-specific rules are emerging. The FTC has signaled that using AI-generated fake reviews without disclosure constitutes deceptive advertising. The FCC adopted rules in February 2024 requiring disclosure of AI-generated audio in political advertising. Several states, including California, Colorado, and Texas, have passed or proposed bills requiring AI disclosure in specific contexts.
Beyond legal requirements, platform policies add another layer. Google's spam policies penalize content that is AI-generated at scale without human review. Meta and LinkedIn prohibit undisclosed AI-generated impersonation of real people.
A simple disclosure policy covers most current requirements and most near-term regulatory risk: label AI-generated content, require human review for content that names real people or makes factual claims, and do not use AI to impersonate humans in marketing or customer communications.
The disclosure cost is low. A one-line label on AI-generated content or a brief note in your content policy takes minutes to add. The reputational and regulatory cost of publishing undisclosed AI content at scale, especially as regulators and journalists pay closer attention, is much harder to recover from.
AI-generated content is not inherently risky, but publishing it without a process is. Build the review step in before you need it, write the contract language before a dispute surfaces, and add the disclosure before a regulator asks why it is missing. Those three steps cover most of the legal exposure for most founders.
