AI Clauses Every Business Contract Should Address

If your last vendor agreement, contractor agreement, or client contract was written more than a year or two ago, it almost certainly says nothing about artificial intelligence. That silence used to be harmless. It is not anymore. AI now drafts marketing copy, writes code, designs graphics, and summarizes confidential documents, often without anyone on your side knowing it was involved. When a deliverable was produced with AI, ordinary questions like “do we own this?” and “who pays if it infringes?” get more complicated.

This guide walks through the AI clauses in contracts that businesses most often need to address. It is general education, not a contract you can paste in, and the right wording depends entirely on your facts. For the big-picture framework, start with our pillar guide on AI and intellectual property.

Disclosure and permission to use AI

The first question a modern contract should answer is simple: is AI allowed here at all, and if so, does the other side have to tell you?

These are two distinct issues. Permission governs whether a contractor or vendor may use AI to produce your deliverables. Sometimes you want them to (it is faster and cheaper); sometimes you do not (the work is sensitive, or you need clean human authorship). Disclosure governs whether they must tell you when they do. Many businesses now ask contractors to disclose whether and how AI was used on a deliverable, to identify the specific tools, and to confirm that a human reviewed the output before delivery.

Why bother? Because you cannot evaluate ownership or infringement risk in work you did not know was AI-generated. A disclosure term turns a hidden risk into a known one you can manage. It is reasonable to address both directions, too: if your own team uses AI, your client contract may need to say so and confirm human review, depending on what your client expects.

Ownership and the human-authorship gap

This is the issue that surprises people most. A normal contract assigns ownership of a deliverable to the buyer. But you cannot own what nobody legally authored, and under current U.S. copyright practice, material generated purely by AI, without meaningful human creative input, is generally not protected by copyright at all.

That creates a gap. You can write a contract saying “all output is assigned to the client,” but assignment only transfers rights that exist. If a chunk of the deliverable is uncopyrightable AI output, there may be no copyright to assign, and that portion can sit in the public domain where anyone, including a competitor, may use it. The contract did not lie; there was simply nothing there to hand over.

Practical contracts address this gap rather than ignore it. They often combine a normal assignment of all rights with a requirement that deliverables involve genuine human authorship and review, and they may require the provider to identify which components are AI-generated so ownership expectations are realistic. We go much deeper on this in who owns AI output, which explains the human-authorship requirement and why “the contract says I own it” is not the end of the analysis.

IP indemnification

Indemnification decides who pays when AI-assisted work triggers a third-party claim, for example, an allegation that the output copied someone else’s protected material.

Here is the trap. A vendor’s contract may include a broad-sounding indemnity, then quietly carve out AI-generated content from it. If the AI output infringes a third party’s rights and that carve-out applies, the loss can land entirely on you, even though you had no idea AI was used or what it was trained on. Many AI vendor agreements also cap their liability low, which limits what an indemnity is actually worth.

So the issue to address is not just “is there an indemnity,” but “does it cover AI output, and is it meaningful?” Businesses often negotiate for IP indemnification that expressly includes AI-generated content, or, at minimum, a clear allocation of that risk with realistic caps and named exclusions rather than an open-ended exposure they never agreed to. This is exactly the kind of term where wording and liability caps deserve a lawyer’s eye.

”Don’t train on our data” and confidentiality

When you feed information into an AI tool, prompts, documents, customer data, that information can leave your control. A standard confidentiality clause written before generative AI may not stop a vendor from using your inputs to improve its own models.

So a growing number of contracts add an explicit no-training term. A representative version says the provider may not use your content, inputs, prompts, outputs, usage logs, or metadata to train, fine-tune, evaluate, or otherwise improve any AI or machine-learning model without your specific written consent. Closely related terms address no retention (delete our data) and no commingling (do not blend our data with other customers’).

This matters for more than privacy. If your confidential information becomes training data, you can lose control over it and, in some cases, weaken its status as a protectable trade secret, which depends on reasonable efforts to keep it secret. A strong confidentiality framework and a clear no-training term work together. If your protection comes from a separate nondisclosure agreement, make sure it actually accounts for AI; our guide on NDAs that hold up covers what makes a confidentiality agreement enforceable in the first place.

Warranties of non-infringement and compliance

A warranty is the other side’s promise that something is true, and it gives you a contract claim if it is not. With AI in the mix, two warranties matter most.

A non-infringement warranty is the provider’s promise that the deliverable, including any AI-assisted portions, does not infringe someone else’s intellectual property. Because no one can fully audit what a model was trained on, providers often resist absolute promises and offer a “commercially reasonable efforts” version instead; where that line lands is a negotiation. A compliance warranty addresses the fast-moving rules around AI: the provider’s promise that its tools and outputs comply with applicable laws, including data-protection and AI-specific regulations that are tightening in 2026.

Warranties about accuracy, originality, and the absence of infringing content are increasingly common, and they pair naturally with the indemnity above: the warranty defines the promise, and the indemnity says who pays when the promise breaks.

A checklist by contract type

The same issues show up differently depending on who you are dealing with. Use this as a starting point for the conversation with your attorney, not as final language.

Vendor / software agreements (the AI tool is the product):

• No-training, no-retention, and no-commingling terms covering your data.
• IP indemnification that expressly includes AI-generated output.
• Realistic liability caps you can live with.
• Warranties on non-infringement, accuracy, and legal compliance.
• Audit rights and breach-notification obligations.

Contractor / freelancer agreements (a person delivering work to you):

• Permission and disclosure: may they use AI, and must they tell you and confirm human review?
• A full assignment of rights, paired with a requirement of genuine human authorship to address the ownership gap.
• A non-infringement warranty and indemnity from the contractor.
• Confidentiality that prevents your materials from being fed into public AI tools.

Client agreements (you are the one delivering work):

• Whether you are permitted to use AI, and what you must disclose.
• A clear statement of what you own versus what you are licensing.
• Liability limits and indemnity caps that match the price of the job.
• Confirmation of human review so you are not warranting more than you can deliver.

For more background on the copyright threads running through all of this, see our copyright topic hub.

The bottom line

AI did not break contract law, but it did expose gaps in contracts written before it existed. The issues worth raising in almost any modern business deal are the same handful: whether AI may be used and disclosed, who actually owns AI-assisted output given the human-authorship gap, who is indemnified when that output draws an infringement claim, whether a vendor may train on your data, and what the other side warrants about non-infringement and compliance. You do not need to memorize clause language, you need to recognize these as questions your contract should answer instead of leaving silent. Because the right wording, caps, and carve-outs turn entirely on your facts, the smart move is to raise these issues early and let a professional draft the terms.

This guide is general educational information about contracting around artificial intelligence, not legal advice, and it does not create an attorney-client relationship. Contract terms turn on the specific facts of your deal and on exact wording, and the law in this area is changing quickly. To draft or review AI clauses for your situation, work with an attorney licensed in your jurisdiction.