Legal Guides

Is AI Output a Product or Content?

By David Meldofsky

Published June 12, 2026

Every major lawsuit against an AI company runs into the same question first. Is what a chatbot says a product, like a car or a medication? Or is it content, like a book or a website post? The answer decides which laws apply and which defenses the company can use. In many cases, it also decides whether the lawsuit survives the company's first request to throw it out.

This guide explains the question in plain English, why it is genuinely hard, and how courts have started to answer it.

This guide goes with our AI Lawsuits overview and the OpenAI case tracker. The full legal treatment of this question is David Meldofsky's Law360 Expert Analysis, Product-Or-Content Question Is Pivotal In AI Litigation, written for a professional audience. This page covers the same ground for non-lawyers.

Why One Question Controls Everything

The two classifications lead to two very different legal worlds.

If AI output is a product, its maker can be sued under product liability law. That is the framework courts use for cars, drugs, power tools, and medical devices. A plaintiff can argue the product was defectively designed, that safer alternative designs existed and were not used, or that the maker failed to warn users about known risks. Critically, none of those claims requires proving the company intended any harm. The focus is on the design choices the manufacturer made.

If AI output is content, two powerful defenses come into play. Section 230 of the Communications Decency Act protects online services from being treated as the publisher of what someone else posted. The First Amendment protects speech. Together, those defenses have ended most lawsuits against internet platforms for decades, usually before any evidence is gathered.

So when a family sues OpenAI over a death they connect to ChatGPT conversations, the first real fight is over which of those two worlds the case belongs in. What happened comes later.

Where the Line Came From

Product liability law grew up around physical goods, and information has always sat outside it. The classic case is Winter v. G.P. Putnam's Sons, a 1991 federal appeals decision about a mushroom encyclopedia. Readers who relied on the book ate poisonous mushrooms and were seriously injured. The court said the physical book might be a product, but the ideas and information inside it were not. So the rules for defective products did not apply. Courts reached similar results for navigation charts and standalone software.

Software embedded inside a physical product has been treated differently. If the software in a car's braking system fails, the car is still a defective product. But those cases involved software bundled into a physical thing. Software sold on its own, like a chatbot subscription, has historically looked more like the encyclopedia than the car.

Why Generative AI Breaks the Old Categories

A chatbot's output is text, which sounds like content. But the company that built the system shapes it from start to finish. It chooses the training data and decides which behaviors get rewarded in training. It adds safety systems on top, and it decides what to do when those systems flag problems.

Three features make AI harder to classify than any earlier software, and each one cuts both ways.

• The output is new every time. A chatbot generates its responses word by word rather than retrieving something pre-written. Defendants say that makes the output speech, not a manufactured item. Plaintiffs respond that the novelty is itself a design choice: the company built and tuned the system that generates it.
• The company did not write the specific words. No engineer at OpenAI typed the sentences a user sees. Defendants say that means the company is not the speaker. Plaintiffs respond that the company designed the system that produced the sentences, which is exactly how design-defect law works: nobody hand-builds each defective unit either.
• The behavior emerges from training. A company can know that harmful outputs will occur without being able to predict any specific one. Defendants say that makes specific harms unforeseeable. Plaintiffs respond that the category of harm was foreseeable, documented internally and externally for years, which is what foreseeability has always meant in tort law.

How Plaintiffs Frame It

The families' strongest argument is about the company's choices. They say the company designed, trained, and released a system that predictably caused specific kinds of serious harm, while safer options went unused. That mirrors how drug and medical device cases work. The defect lies in the design decisions, the testing, the warnings, and how the company responded once problems surfaced. Those are all choices the maker made, and a maker's choices are what product liability law has always judged.

The complaints in the current OpenAI cases make several overlapping claims built on that argument. Some are designed to survive even if the product question goes against the families:

• Defective design claims say the model was trained to be so agreeable that it affirmed and followed vulnerable users. They say safer designs were available and went unused.
• Failure of safety operations claims allege internal threat-detection systems flagged dangerous conversations and the company's response was inadequate. This theory asks only whether stated safety practices matched actual conduct, not whether the output is a product.
• Failure to warn claims allege the product was marketed as broadly safe, including for emotionally sensitive use, despite internal knowledge that it performed unreliably in exactly those situations.
• Negligent entrustment claims, with roots in cases about cars and firearms, allege the company kept providing access to a user it had reason to know was dangerous. The claim targets the access decision, not the content, which is why it may survive even a ruling that the output is protected content.

Section 230, in Plain English

Section 230 was written in 1996. Its core rule says an interactive computer service cannot be treated as the publisher of information provided by another person. It is the reason platforms generally cannot be sued over what their users post.

AI companies argue the rule fits chatbots too. In their view, the user's prompt is information from another person, and the chatbot's answer is a reply to it. The families argue there is no other person, because the system itself writes the words. They also say the law was never meant to shield a company from the results of its own system's design.

Which reading wins is one of the central open questions in AI law. The answer will shape future Section 230 cases well beyond chatbots.

The First Amendment Argument

Defendants also argue that algorithmically generated text is speech protected by the First Amendment, drawing on cases that recognized protection for data and computer code. Plaintiffs respond that holding a manufacturer responsible for a system's design is not the same as punishing a publisher for its message. Courts have so far been reluctant to resolve that question early in a case, which matters, because the longer it stays open, the more evidence plaintiffs can gather.

What the Garcia Ruling Did

The most consequential ruling so far came in Garcia v. Character Technologies, a Florida federal case brought by Megan Garcia after her 14-year-old son's suicide following extensive interactions with Character.AI chatbots. The defendants moved to dismiss on the three grounds described above: the chatbot is a service rather than a product, Section 230 applies, and the output is protected speech.

In May 2025, the court refused to dismiss the core product liability and negligence claims. It left open whether the chatbot is a product. It found the family had made a believable case that it might be, and that the conduct could be treated as design rather than publishing. It also found the First Amendment question could not be decided that early.

The ruling is an early step, and the case did not reach a final decision on these questions. It was still the ruling the families needed. It lets the question be decided on the evidence, including internal documents, training decisions, and safety records. The full case guide is at Garcia v. Character Technologies, with the other cases in our Character.AI lawsuits overview.

How the OpenAI Cases Test the Question

The current OpenAI cases come at the question from several angles at once, so the families do not depend on any single theory. Raine v. OpenAI carries the design-defect theory on its strongest alleged facts. The Tumbler Ridge school shooting suits carry the safety-operations theory, which does not depend on the product question at all. The FSU shooting case carries negligent entrustment in its most traditional form. The Turner-Scott overdose case carries failure to warn in a medical information setting.

Florida's June 2026 suit shows a state pressing the same first question through consumer protection law. That suit is covered at Florida v. OpenAI, and other state actions are tracked at States Suing AI Companies.

Rulings on OpenAI's requests to dismiss these cases, expected through late 2026, will begin to answer the question. No single ruling will settle it. The pattern across the rulings, which theories survive and which courts adopt which framing, is what will define the terrain.

Common Questions

Why does it matter whether AI output is a product or content?

Because the classification decides which body of law applies. Product status opens the door to design defect and failure-to-warn claims, the framework used for cars and drugs. Content status opens the door to Section 230 and First Amendment defenses, which have historically ended platform lawsuits before evidence is heard.

Has any court decided whether an AI chatbot is a product?

Not as a matter of law. In May 2025, the court in Garcia v. Character Technologies found the family had made a believable case that a chatbot was a product. That let the case move on to gathering evidence. That is the furthest any court has gone, and it was an early ruling in the case.

Does Section 230 protect AI companies like OpenAI?

It is unresolved. The defense reading treats the chatbot's answer as a reply to user-provided information. The plaintiff reading says the system itself generates the words, so there is no third party to point to. Courts are testing both readings now.

Can a lawsuit against an AI company succeed even if courts say the output is content?

Possibly. Negligent entrustment, failure to warn, and safety-operations theories each target company conduct rather than the content itself, and each may survive an adverse ruling on the product question.

Sources and further reading

• David Meldofsky, Product-Or-Content Question Is Pivotal In AI Litigation, Law360 Expert Analysis (June 2026)
• Lawsuit Informer: OpenAI Lawsuits Hub and Case Tracker
• Lawsuit Informer: Raine v. OpenAI Case Guide
• Lawsuit Informer: Character.AI Lawsuits
• Lawsuit Informer: States Suing AI Companies
• Lawsuit Informer: Product Liability Lawsuits

Educational commentary only. Not legal advice. No attorney-client relationship is created.