AI video tools are now part of normal production, and disclosure is part of normal editing. The practical rule is straightforward. If a reasonable viewer would change how they interpret the video after learning how a scene was made, say so.
That covers synthetic voices, generated presenters, and invented footage presented as real events. It usually does not cover background removal, color work, or captioning, which are refinements of material that genuinely existed.
The judgment call sits in the middle, and most disputes happen because nobody decided the rule before publishing. Agree on the standard while the project is calm, not after the first angry comment.
Trust is the asset you are protecting. Audiences will accept generated footage when they know it is generated, and they will feel betrayed by the same footage once they discover it was hidden. The work is identical. Only the framing changes the outcome.
A label buried in a description does not travel with a clipped video. Put disclosure where the content travels, which for short form often means on screen. Keep it plain and short, because a cryptic notice is worse than none at all.
Platforms increasingly add their own generated content markers, and those labels can conflict with what you would write yourself. Check the current rules before you upload, and keep your own note consistent with them rather than fighting them.
Timing matters too. A note at the end of a video reaches almost nobody, while a brief mention near the start sets the frame before the viewer has formed an opinion.
Documentaries and news carry a higher duty than entertainment. When the subject is verifiable fact, the bar for labeling grows, and a casual mention is rarely enough for footage that pretends to record a real event.
Every generated asset raises two questions. Do you have the right to use the inputs, and do you have permission to depict the people involved? Likeness is the sharper risk, since a synthetic version of a real person can mislead even when no money is exchanged.
Keep records of what you generated, with which tool, and what you supplied as reference. When a client asks for proof of provenance, a clear log is the difference between a calm answer and a rebuild.
Spokespeople and public figures need extra care. A generated version of a recognizable face carries implications a generic stock model never would, and the permission you need is usually explicit rather than implied.
Training data is the murkier question. You rarely know what a model learned from, so the honest position is to avoid claims you cannot support and to keep records of what you supplied yourself.
Put the rules in the contract, not just in a document nobody reads. A client who agrees to disclosure terms before work starts will not fight you about a label three weeks later, and that agreement protects the relationship as much as the video.
Build the review into the schedule. When disclosure and consent are checked during preproduction, they cost almost nothing, and when they are discovered at the end they turn into a rush that nobody wants to pay for.
Disclosure is not an apology. It is part of the craft, and audiences reward the honesty.
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