Prepared with AI assistance and reviewed for clarity, relevance and unsupported claims.
An AI-assisted UGC review should ask more than whether a video looks polished. It should establish what viewers are being invited to believe: are they seeing a product demonstration, an illustrative scene, a scripted presenter or a genuine customer describing an actual experience?
Those categories are not interchangeable. A conversational style does not make someone a customer, and a realistic generated scene does not establish that an event occurred. A Moroccan shop can use AI to help prepare content while keeping those distinctions clear.
1. Classify the content before reviewing individual lines
Write a plain-language description of the asset’s purpose before production begins. “A merchant demonstration of how the bag closes” is different from “a customer explaining how the bag performed during travel.” The second requires a real experience and a source for that account.
- Product demonstration: shows a feature or manipulation using identified evidence.
- Scripted presentation: a presenter explains approved facts without claiming to be a customer.
- Illustrative scene: depicts a possible setting or scenario, not an observed customer event.
- Customer testimony: conveys an actual person’s experience, supported by its source and appropriate permission for the intended use.
A single video can contain more than one category. Mark the boundaries. A real close-up of a product followed by a generated lifestyle sequence does not turn the generated sequence into evidence.
These are editorial distinctions for truthful communication, not a substitute for checking applicable rules or platform requirements for a particular publication.
2. Record where meaningful elements came from
Keep a short provenance record: where the footage, voice, script, quotations and product images originated, and what was changed. The record should let a reviewer distinguish captured material from generated or substantially altered material without guessing from appearance.
For real footage, note who supplied it and which product it shows. For a quotation, retain the source and approved wording. For synthetic elements, describe what was generated and whether any real person’s likeness or voice was involved. Record the permission basis and intended uses where relevant; unresolved permission should block release.
You do not need to collect unrelated personal information. The goal is to substantiate the content and manage its use, not build a detailed profile of a contributor.
Store these records with the asset’s approval package. A clear UGC library and publishing handoff keeps the explanation attached when files move from an editor to a publisher.
3. Audit claims of personal experience
Review every first-person statement, including captions, subtitles and text overlays. “I ordered this last month” asserts a purchase. “I use it every morning” asserts repeated use. “My customers keep asking for it” asserts customer behaviour. These are factual claims, not harmless ways to make a script sound natural.
In a hypothetical example, a shop prepares a video for a desk organiser. The draft combines genuine product close-ups with an AI-generated home-office scene. Its synthetic narrator says: “I bought this for my desk, and it finally keeps everything organised.” No customer supplied that account.
The reviewer removes the invented purchase and outcome. A replacement might be:
“This illustrative desk scene shows one possible arrangement. The product close-ups show the compartments of the organiser sold by the shop. Check its dimensions against the items you want to store.”
The replacement is acceptable only if the close-ups and dimension information support it. Avoid converting the invented experience into an equally unsupported general claim such as “keeps every desk organised.”
4. Check what synthetic images imply about the product
Words are only part of the review. Generated scenes can alter compartment counts, colours, proportions, packaging or how an object behaves. A synthetic organiser that accommodates a large laptop may imply a capacity the real product does not have.
Compare the scene with approved product references. Ask whether a reasonable viewer could mistake a generated feature or action for a demonstrated capability. If so, replace the scene with suitable real footage, correct it and re-review, or remove it.
A disclosure does not make an inaccurate product depiction useful. “AI-generated illustration” can explain the origin of a scene; it does not justify showing the wrong contents or an unsupported function.
Real footage is usually the clearer choice when the buying question concerns fit, texture, operation or exact contents. Synthetic backgrounds may provide context, but they require checks for misleading scale and visual changes. For products with several versions, also check product variant accuracy.
5. Make descriptions clear where viewers encounter the claim
Choose audience-facing wording that describes the relevant distinction. “AI-assisted” alone can be too broad: it might mean the script was shortened, or that the apparent person and setting were generated.
Depending on the actual content, useful descriptions include “AI-generated illustrative scene; product close-ups filmed separately” or “Scripted product presentation, not a customer testimonial.” Do not use a description that understates what was generated.
Place the explanation where it can inform the viewer’s interpretation. If a clip will circulate without its original caption, essential context should remain within the clip. A label hidden after a long sales caption may not counter the immediate impression of a personal endorsement.
There is a production trade-off: visible explanations take space and can interrupt a casual visual style. Solve that with concise language and simpler creative choices, not by removing necessary context. If a concept only works when viewers mistake a synthetic person for a customer, redesign it.
6. Use a release decision with explicit blockers
Give the reviewer three options: approve, request changes or hold pending evidence. Approval should apply to the assembled video and its publication copy, not just a script that may change during editing.
- Confirm the content category and any mixed sections.
- Check sources for quotations and experience claims.
- Inspect synthetic scenes against the actual product.
- Verify that descriptions remain understandable without sound.
- Check that the caption does not restore a removed endorsement.
- Record the approved version, reviewer and permitted use.
Hold content with an invented endorsement, unresolved source permission or materially inaccurate depiction. Request changes when the underlying evidence is sound but the presentation is ambiguous. Any later change to narration, synthetic imagery or experience claims needs another review.
AI can flag suspicious phrases, but it cannot establish whether a purchase or customer experience really happened. Assign that decision to someone who can inspect the records. If a misleading asset is discovered after publication, pause planned reuse and review the live placements for correction or removal.
To discuss how these checks could fit your UGC production and publishing workflow, contact FlowAgent.