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Why “AI liability” has no one-size-fits-all answer
“AI caused harm” describes an outcome, not a complete legal claim. A decision-maker has to connect the harm to an actor and conduct under a legal route that applies in the relevant jurisdiction. Product liability is one possible route, but contract or another applicable law may also matter. Which route is available—and what it requires—cannot be determined from the fact that AI was involved alone.
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Roles can also overlap in a real system. A provider, deployer, and user are useful starting points for asking what each party did, not a shortcut to assigning fault. The AI system’s inclusion within a regulatory framework likewise does not decide the result of an individual liability claim.
Which actors may be relevant?
| Actor | Question to investigate | What the role alone establishes |
|---|---|---|
| Provider | Who supplied or developed the AI system, and what part did that party play in the alleged harm? | The EU AI Act includes providers among the roles within its scope. Under the revised EU Product Liability Directive, software developers or producers, including AI system providers, are addressed as manufacturers. Neither point alone establishes liability in a particular case. |
| Deployer | Who put the system to use in the setting where the harm occurred, and what did that party do? | The EU AI Act includes deployers within its scope. That is not a blanket rule making deployers primarily liable for every AI-related harm. |
| User | Who interacted with the system or acted on its output, and what connection did that conduct have to the harm? | The label “user” alone does not establish a particular liability outcome. The applicable route and jurisdiction still matter. |
| Product manufacturer | Was a product-related claim brought against a manufacturer or another party treated as a manufacturer under the applicable law? | The revised EU Product Liability Directive includes software in its definition of product and addresses AI system providers as manufacturers. That product-liability route does not make deployers primarily responsible for every AI harm. |
These are investigative questions, not a ranking of likely defendants. More than one actor may need to be examined, and the relevant legal rules vary by jurisdiction.
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How the EU AI Act differs from product liability
The EU AI Act and the revised EU Product Liability Directive address different legal questions. The AI Act identifies several roles within its regulatory scope, including providers, deployers, importers, distributors, and certain product manufacturers. Its general application date is August 2, 2026. Specified high-risk-system requirements have later application dates, including December 2, 2027 and August 2, 2028, depending on classification.
The Act’s scope and application dates should not be read as a universal compensation rule or as an assignment of primary liability to deployers. Whether an individual party is liable for a particular harm requires analysis under the applicable legal route and jurisdiction.
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The revised EU Product Liability Directive, Directive (EU) 2024/2853, expressly includes software in its definition of a product and addresses software developers or producers, including AI system providers, as manufacturers. It is a product-liability route; its coverage does not establish that every AI harm is a product-liability case.
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Which dates matter under the revised EU Product Liability Directive?
As of October 4, 2026, the directive’s two key dates are close together but refer to different things:
- December 8, 2026: the directive applies to products placed on the market or put into service after this date.
- December 9, 2026: the deadline for EU Member States to transpose the directive into national law.
The first date concerns which products fall within the directive’s application rule; the second is a deadline for Member States. They are not interchangeable. For a specific dispute, the relevant product date and the national law in force must be checked rather than assuming that one date answers both questions.
How to assess a specific AI-harm incident
- Describe the harm precisely. Record what happened, when it happened, and what loss or injury is being claimed. “The AI was wrong” is not a substitute for identifying the consequence.
- Map the people and organizations involved. Identify the provider, the party that deployed the system, the person who used or acted on its output, and any relevant product manufacturer. Record what each actually did rather than relying only on job titles or labels.
- Identify the possible legal route. Ask whether the issue is being considered as product liability, contract, or another applicable legal claim. Do not assume that the presence of AI makes one route exclusive.
- Establish jurisdiction and timing. Determine which jurisdiction’s rules may apply and the relevant dates, including when the product was placed on the market or put into service if the EU directive is at issue.
- Separate regulatory scope from the liability conclusion. Being within a law’s scope may be relevant, but it does not by itself prove which party owes compensation in the incident.
This framework helps organize the questions; it cannot determine the outcome without the facts and applicable national law.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What can—and cannot—be concluded about US claims?
There is no universal AI-liability rule established here for the United States, and descriptions of particular US lawsuits or official statements should not be treated as verified without primary court records or a transcript. A case’s jurisdiction and procedural posture matter: a claim being filed is not the same as a court deciding that a party is liable. Case-specific conclusions require checking the relevant docket and governing law.
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