What to tell clients about using AI in delivery
Contract language covering AI production, where audience disclosure is actually required, and the framing that sells iteration speed over cheap labour.
The account-losing event is almost never a client discovering that you use AI. It's a client discovering it from somewhere else: a synthetic-media label appearing on a post they published, their agency-of-record flagging an asset during a compliance review, a marketplace listing pulled for an undisclosed AI design, or a comment thread they have to answer and can't. At that point the conversation is not about production methods. It's about what else you didn't mention.
The fix is dull and takes one clause plus one paragraph in the kickoff deck. What makes it feel hard is that two completely different disclosures get collapsed into one worry.
Two disclosures, and they are not the same thing
Client-facing disclosure is commercial. It answers "how is this made" for the person paying you. Nobody outside the contract ever reads it. It is entirely within your control and there is no external body enforcing it — which is exactly why leaving it out feels safe and later isn't.
Audience-facing disclosure is compliance. It answers "was this synthetic" for the person watching, and it is governed by platform policy, marketplace rules, and in some jurisdictions statute. It is not your decision, it is a rule you either follow or breach, and in most cases the account it breaches is the client's.
These have different failure modes and different owners, and the contract has to assign both. The distinction between profile-level and post-level disclosure matters here too: telling your audience once, in a bio, is a different commitment from labelling each asset, and clients frequently assume the first covers the second. It doesn't.
Where audience disclosure is actually required
| Surface | Requirement | Practical note |
|---|---|---|
| YouTube | Disclose altered or synthetic content that could mislead, via the upload toggle | Toggling it does not by itself cost monetisation or reach |
| Meta (Facebook, Instagram) | AI content permitted but must be original to the creator and labelled | Runs through the unified Content Monetization Program |
| Etsy | Disclosure required in the listing | Permitted since 2024, and applies to AI-assisted as well as fully generated |
| Amazon Merch on Demand | AI disclosure required since 2025 | Third-party guides report new accounts capped at 10 AI-generated designs a day against 25 non-AI; verify current limits in the dashboard |
| Redbubble | Permitted under standard content policy | No dedicated AI disclosure field |
Two things clients get wrong about this table. First, the YouTube toggle is not a penalty. The persistent belief that disclosing suppresses reach costs more accounts than disclosing ever has, because it pushes people into not labelling things that plainly needed a label. Second, monetisation risk on YouTube comes from a different rule entirely: the July 2025 rename of "repetitious content" to inauthentic content targets output made with generic or unoriginal templates that gives the impression of mass production, and separately excludes AI personas delivering health, legal or financial advice. Original AI work with an invented character and narrative is explicitly monetisable. Templated volume is the exposure, not the AI.
If a client publishes across several platforms, the labelling obligations stack rather than substitute — one asset can need three different disclosures on five destinations, and sponsorship disclosure sits on a separate axis again.
There is one rule with no exception anywhere: never market AI-generated work as handmade. On the marketplaces that is a permanent-ban trigger, and it is the one misstep that cannot be argued down after the fact.
The copyright clause nobody writes and everybody needs
The US Copyright Office position is that purely AI-generated images with no meaningful human creative input are not copyrightable. Human arrangement, composition edits and typography are what create a protectable work.
That has a direct contractual consequence most delivery agreements ignore: you cannot assign what you do not own. A standard "all deliverables and all rights therein are hereby assigned to Client" clause, applied to a raw generation, is assigning something that may not exist. If the client later needs to enforce against a copycat, they discover the gap at the worst possible moment.
The workable position is to say what is actually true — the deliverable includes human selection, arrangement, editing and typography, those elements are assigned, and protection over raw generated elements is uncertain under current law. Clients with in-house counsel will respect the accuracy. Clients without will never read it. Either way you have not promised something you can't deliver. The wider copyright and safety picture is worth reading before you draft it.
The clauses
Draft language to take to a lawyer, not to sign as-is. This is not legal advice and your jurisdiction will have its own view.
Production methods. "Supplier uses generative AI tools as part of its production process, including for image, video, voice and music generation, together with human direction, selection and editing. Client acknowledges and consents to this." One sentence, in the main agreement, not an annex. The point is that consent is on the record and dated.
Assignment, scoped honestly. Assign the deliverable as a whole, expressly including human-authored elements — sequencing, edit decisions, typography, composition — and state that protectability of individual generated elements is uncertain under applicable law. Do not warrant copyright in raw output.
Labelling responsibility. Name who applies platform AI labels. If the client publishes, it's theirs and you supply the information they need to do it. If you publish on their behalf, it's yours. Unassigned, it becomes an argument after a strike.
Likeness and voice. Warrant that no deliverable replicates a real identifiable person's likeness or voice without written consent, and require the client to provide releases for any of their own staff or customers appearing in supplied material. This is the clause that stops a "just make it look like our founder" request from becoming your problem.
Third-party material. Cover what happens to client-supplied assets: they warrant they have the rights, you warrant you won't train on or reuse them outside the engagement.
Usage rights, priced separately. Borrow the structure the UGC market already settled on, where paid-media usage and buyouts are priced above the production fee rather than bundled into it. Usage rights in creator contracts is the same negotiation with different parties, and the mistake — handing over unlimited use at the production price — is identical.
If you white-label through another agency, the chain gets longer and the consent has to travel with it. White-labelled AI content means the end client's consent has to be obtained by someone, and "the reseller handles it" is not a thing you can verify after a complaint.
Sell iteration, not cheap labour
The framing decision matters more commercially than the disclosure does.
If you present AI as the reason your price is low, you have anchored the entire relationship on price and handed the client a permanent lever. Every renewal is now a negotiation against whoever is cheaper this quarter, and someone always is. Worse, you've told the client the value is in the tool, which is a thing they can buy directly.
The defensible framing is volume and iteration count, because that is a capability a shoot cannot match at any budget. Thirty hook variants tested against one body is not a cheaper version of a shoot — it's a thing that does not exist in a shoot. A same-day recut after a soft launch is not a discount, it's a different response time. The pitch is "you will find out which version works before your competitor has finished scheduling their edit," and the price sits wherever that outcome is worth.
The economics behind that claim hold up. Iterating in the editor is genuinely cheap: 480p preview passes carry no credit charge, subject to a short per-user cooldown, and the single charge lands on the final export regardless of timeline complexity. So the thirty-variant test is not a favour you're absorbing, it's how the pipeline actually behaves — which is why it's an honest thing to sell rather than a loss leader.
None of that requires hiding the method. It requires putting the method in the part of the conversation where it's an advantage instead of the part where it's an admission. A written AI policy does that job on the client's side, and a disclosure line that doesn't read like a warning label does it on the audience's.
FAQ
If disclosure doesn't hurt reach, why does everyone believe it does?
Because two effects get attributed to one cause. Accounts publishing templated, high-volume AI output do see distribution and monetisation problems, and those accounts also label their content, so the label gets blamed. The policy language points at the other variable: the exposure is content that reads as mass-produced from generic templates, not content that carries a synthetic-media tag. Original work with a disclosure toggle on is a normal upload.
Do I need to disclose AI use to a client who never asked?
Yes, and it's cheaper as a line in the agreement than as an answer to a question six months in. The asymmetry is the whole argument: disclosing costs a sentence, and being found out costs the trust that every subsequent invoice depends on. Clients who would have objected will object early, which is information you want before you've built a delivery pipeline around them.
What do I say when a client asks me to keep it quiet publicly?
Separate the two disclosures for them. Their marketing does not have to lead with "made with AI" — nobody's does. What is not optional is platform labelling where the rules require it, and the reason is that the strike lands on their account, not yours. Framed as protecting their asset rather than satisfying your conscience, this conversation almost always lands.
Does any of this apply to voice clones of the client's own staff?
It applies harder. Cloning a real person's voice needs that person's written consent, held on file, and it should survive their departure — a clause covering what happens to a cloned voice when the employee leaves is the one everybody forgets. Consent from the employer is not consent from the individual, and in a growing number of jurisdictions the individual is the only party who can give it.