Sora is OpenAI’s text-to-video model, and like Runway, Google Veo and Kling it can turn a written prompt or a still image into short, realistic clips. Before a marketing team publishes anything made with it, they need written rules on likeness, copyright, disclosure, brand accuracy and review. Without those rules, the speed of generation simply moves risk downstream to legal and customer support.
What does Sora actually do well, and where does it fall short?
Sora generates video from text, from images, and from existing clips that you want to extend or remix. It is strongest at atmosphere: a rainy street in Istanbul at dusk, slow drone-style moves over a coastline, abstract product mood shots. Those are the shots that used to need a location budget or stock footage licences.
It is weaker at precision. Hands, readable text on signs, consistent faces across cuts and accurate physics still break in many outputs. Product packaging is the biggest problem for brands, because the model invents label details. A bottle that looks almost like yours is worse than no bottle at all.
Clip length and resolution limits have changed several times, so check the current plan inside the app rather than trusting an old article. At the time of writing, most teams use Sora for short sequences that are then cut together in a normal editor such as Premiere Pro or DaVinci Resolve.
Which risks should a brand rule out before the first prompt?
Most problems with AI video are not technical. They come from someone generating something that the company never agreed it was allowed to publish. List the risks first, then write one rule for each.
- Likeness: generating a real person, including employees, without written consent.
- Third-party IP: prompts that name a film, artist, character or competitor brand.
- Product misrepresentation: AI-made packaging, features or results that the real product does not have.
- Undisclosed synthetic media: viewers believing a staged scene is real footage.
- Data leakage: uploading unreleased product images or client material to a consumer account.
- Platform rejection: ads that break Meta, TikTok or YouTube policies on manipulated media.
Each item maps to a person who signs off. Likeness and IP go to legal or the account lead. Product accuracy goes to the product owner. Disclosure goes to whoever owns the channel.
How should you label AI-generated video?
OpenAI adds C2PA content credentials and a visible watermark to Sora outputs, which helps platforms detect synthetic media. Do not treat that as your disclosure. Watermarks can be cropped during editing, and metadata is often stripped when a file is re-exported or uploaded.
Meta, TikTok and YouTube each ask creators to label realistic altered or synthetic content, and each has a toggle for it at upload. YouTube shows the setting as “Altered or synthetic content” in the upload flow. Make switching it on part of the publishing checklist, not a personal judgement call.
In the EU, the AI Act adds transparency duties for deepfakes, meaning content that resembles real people, places or events and could be mistaken for authentic. If you run campaigns in Europe, the safest default is a short on-screen or caption note whenever a scene could pass as real footage.
What does a practical governance policy contain?
A one-page policy beats a forty-page one that nobody reads. It should answer who may use the tool, on which account, for what, and who approves the result. Keep it next to the brand guidelines so designers see both together.
Access and accounts
Use a business or team plan that the company controls. Personal accounts mean you cannot see what was generated, cannot remove access when someone leaves, and cannot check the data terms. Write down which plan you use and what its terms say about training on your inputs.
Prompt and asset rules
Ban prompts that name living artists, film titles, celebrities or competitor brands. Ban uploads of client material unless the contract allows it. Keep a shared prompt library so that good prompts are reused and risky ones are visible.
Review and approval
Every clip that goes public gets two checks: a brand check (colours, logo, tone, product accuracy) and a compliance check (consent, IP, disclosure, platform policy). Log the prompt, the date, the reviewer and the final file name. If a complaint arrives six months later, that log is what you will need.
How Alien Road applies Sora and AI video generation
In a typical engagement our video team starts with discovery: which shots in the storyboard are mood, which are product, and which involve people. Only mood and background shots go to a generator. Product shots stay with real footage or 3D renders, because invented label details are not acceptable.
Setup means a company-controlled account, a prompt library per client, and a review sheet with the two checks above. We generate several variants, cut them in a normal editor, and add the real product, logo and legal text as separate layers so the model never draws them.
For measurement we compare AI-assisted cuts against conventional ones on the same audience, usually on hook rate and cost per view, and report both production hours and media results. If an AI cut performs worse, the report says so, and the next brief changes.
Which limits should you accept rather than fight?
Some shots are simply not a fit yet. Long dialogue scenes, testimonials, anything with a real customer, and tight product demos still belong to a camera. Trying to force them through a generator wastes more hours than it saves.
Consistency across a series is the other hard limit. Keeping the same character, set and lighting across ten clips takes many retries. Many teams solve this by using AI only for b-roll and transitions, and keeping hero shots real.
- Good fit: backgrounds, abstract mood, seasonal transitions, concept boards for client approval.
- Possible with care: stylised explainers, animated scenes without real faces.
- Poor fit: testimonials, product close-ups, legal claims, anything showing a real person.
Where to start this week
Pick one upcoming campaign and mark every shot in its storyboard as mood, product or people. Draft the one-page policy using the six risks above, and get legal and the channel owner to sign it. Then move one mood shot to Sora, run it through both checks, and publish it with the platform disclosure switched on. One controlled test tells you more than a month of internal debate.
Keep reading: Video Production · AI Marketing