How to tell if a video is AI-generated, and what your customers notice

Most pages on this topic are written for people who watch video. This one also speaks to the person who publishes it. If you run a small business and use AI to make clips, you are on the other side of the screen, and you want to know what your customers will notice and how they will feel about it.

The visual signs that still show up

AI video models (software that turns a text description or a still image into moving pictures) get better every few months, so any list of signs goes out of date. These are the ones that most sources agree on, roughly from most to least reliable.

1. Text and logos. Signs, labels, packaging, price tags and brand marks often come out as soft, shifting or nonsense letters. They may change from one frame to the next. This is the most reliable sign.
2. Hands and fingers. Look for extra or fused fingers, hands that hold an object oddly, or fingers that pass through things. If a clip of your own shows this, see how to fix hands, text, faces and physics.
3. Teeth, eyes and blinking. Teeth can blur into one block. Blinking may be missing, too regular or too slow. Eyes may not track the action.
4. Lip sync. Lip sync means the mouth matching the words. Watch whether the mouth shapes match the sounds, especially on b, m and p. Drift or a "floating" jaw is a clue.
5. Skin and hair. Skin that looks airbrushed with no pores, and hair edges that shimmer or merge with the background.
6. Light and shadows. Shadows that point the wrong way, reflections that do not match, or light that changes for no reason between cuts.
7. Background warping. Straight lines that bend when the camera moves, people or objects that melt, appear or vanish behind the main subject.
8. Physics and cuts. Liquids that pour wrong, fabric that moves like rubber, feet that slide on the floor. Very fast cuts can also hide flaws, and a long video made of many short clips deserves a second look.

Slow the clip to half speed and step through frame by frame around anything that moves fast. Errors that hide at normal speed can show up in one frame.

The audio signs

• A voice that is a little too even, with no breaths, no mouth noise and no small stumbles.
• Flat emotion where the words call for feeling.

Cloned voices (a copy of a real person's voice made from a sample) can be very close. Treat audio as a clue, not as proof.

Context checks that work better than staring

Eyeballing the pixels is the weakest method. These checks are often stronger.

• Source. Who posted it first? An account that is new, posts only dramatic clips, or has no real history is a warning sign.
• Corroboration. Is the same event covered by news outlets, other witnesses or official channels? A big event with one clip and no second source deserves doubt.
• Reverse search. Take a still frame and run it through an image search. Often you find the original, or find that the clip was posted months ago as something else.
• Labels. Many platforms add an AI label. Check the caption, the description and the player.

A real video can look strange (low light, heavy compression), and an AI video can look perfect. Looks prove nothing either way.

Do AI video detectors work?

There are many free and paid detection tools, and some look convincing. I would not use one as proof, for three reasons.

• Accuracy claims come from the sellers. Ranking guides from vendors (a video editor and a voice-detection company) claim ranges such as 70 to 95 percent and 94 to 98 percent. Neither gave the test set, the method or the false-positive rate (how often a real video is wrongly flagged). I know of no independent benchmark. Treat these numbers as marketing, not measurement.
• Many tools focus on audio or on faces, so a clip with neither may slip through.
• The arms race. When a detector learns a pattern, generators learn to avoid it. A tool that worked last quarter may not work now.

A detector result of "likely AI" is a reason to look closer. A result of "likely real" is not permission to trust the clip.

Provenance beats guessing

Provenance means a record of where a file came from. The main standard is C2PA, which stands for the Coalition for Content Provenance and Authenticity. Files that follow it can carry Content Credentials, a signed note that says which tool made or edited the file. Some platforms read these notes and add a label. TikTok's help center is reported to say it requires a label on realistic AI content and labels uploads that carry C2PA data. Check TikTok's current help page before you rely on this.

Two limits to know. First, the note can be stripped out when a file is re-saved or screen-recorded, so a missing credential tells you little. Second, a present credential tells you how the file was made, not whether what it shows is true. Some AI tools say they may embed invisible markers in their output. For example, Higgsfield, a platform that gives access to several AI image and video models, says in its terms (section 6.4) that it may embed machine-readable markings, and that it does not promise a marking is applied to every output or persists. Free-account output on Higgsfield also carries a visible watermark. Visible watermarks are easy to crop, so absence proves nothing.

What customers actually think

Here is what two surveys found. Both have limits, which I note.

YouGov (a market research company) surveyed 1,046 Australian adults between 7 and 12 May 2026. It found that 45 percent would trust a brand less if its ads were mainly AI-made, and 86 percent said such ads should be disclosed (55 percent said always). Only 34 percent were confident they could tell. Limit: it is one country and one survey.

IAB (the Interactive Advertising Bureau, a trade group for online advertising) and Sonata ran a study reported by the trade site Tubefilter in January 2026. It found that 82 percent of ad executives believed Gen Z and Millennial consumers feel positive about AI ads, while only 45 percent of consumers said they do. It also found that 73 percent of consumers said clear disclosure would increase their likelihood to buy or make no difference. Limit: this is an industry-group study, and the figures come from the Tubefilter report, not the IAB report itself.

Put the two together carefully. In the YouGov survey, few people were confident they could spot AI, yet many said they would trust a brand less if it leaned on it. And most say they want to be told. So a clip can pass inspection and still cost you trust if the customer later learns it was AI and nobody said so.

A 10-minute self-audit for your own clip

Run this on any AI clip before you publish it.

1. Watch it on a phone, muted, at normal speed. Write down anything a stranger might flag.
2. Watch it again with sound. Note voice, breaths and sync.
3. Pause on every shot that shows text, a logo, your product, a price or a person's face. Zoom in.
4. Step frame by frame through any fast hand movement.
5. Check that your product looks the way it does in real life: the shape, colour, size and number of parts.
6. Ask someone who has not seen it to watch and say what felt off. Do not tell them it is AI first.

Pass: no one flags text, hands, the product or the logo. Fail: any of those gets flagged. For a fuller review list, see the AI video quality check.

Customers judge the weak spots first: your product, your logo, your prices and your people. That is a good reason not to generate those four things. Film the product, add the logo and prices in an editor as real text, and use AI for background, mood and cutaways. My page on when not to use AI video goes through what to keep real, and AI video vs stock footage vs filming yourself helps you choose the source for each shot. Free tools often add a visible mark, covered in free AI video generators: watermarks, limits and rights.

Disclosure habits that protect trust

Here is the ladder I use. It is a habit, not a legal rule.

• Always say so when the clip shows a realistic person, a real-looking event, or a voice that sounds like a real person.
• Optional for obviously stylised art, abstract motion or background texture.
• Never use AI for testimonials, reviews or claims about results. The US Federal Trade Commission (FTC), which regulates advertising, says in its Q and A on the consumer reviews rule that fake or false testimonials are prohibited, and courts can impose civil penalties for knowing violations. The same page says there is no blanket ban on AI avatars in marketing.

Wording that works is short and plain: "Visuals made with AI and reviewed by our team." Put it where people will see it: on the video, in the caption or in the description. Do not bury it in a footer.

Keep your records. Save the project file, the prompts and the export date for each AI clip. If a customer or a platform asks, you can answer in minutes. For agency work, my page on whether agencies should disclose AI use covers client conversations.

Rules to know

This is information, not legal advice. Rules vary by country and platform and change often, so check the official page for each.

• YouTube requires creators to disclose realistic altered or synthetic content. Minor edits, captions, upscaling and voice cloning of your own voice are exempt. The label may show on the player or in the description, and repeated failure to disclose can lead to a manual label, removal or loss of Partner Program access.
• TikTok has a help page on AI labels. Check it directly for the current rules.
• EU AI Act, Article 50. According to a text mirror of the act, it applies from 2 August 2026. Providers must mark synthetic output so machines can read it, and people who use AI to make deepfakes must disclose it. If you sell to EU customers, read the article or ask your adviser.
• FTC. Fake testimonials are banned, as described above.

Meta, the company behind Facebook and Instagram, has also said it applies its own "AI info" label using its own tools and industry signals. Meta changes its policy often, so check its current rules before you rely on this.

How I'd approach this

As a viewer, I would trust sources and second confirmations before pixels. As a publisher, I would assume a careful customer might spot my weak points, so I would film what matters (the product, the prices, the people) and use AI where a mistake would not cost trust. I would run the self-audit on every clip, keep the prompt log, and tell people plainly when the picture is not real. If you want a repeatable review step and a shared library for your clips, Blur Studio builds those, and you can talk to me here.