How to Tell If a Video Is AI-Generated
Last year, a finance executive in Singapore transferred $25 million to a fraudster's account after a video call with his "CFO." Every person on that call was a deepfake. This guide walks you through what to look for, what tools to use, and what to do if you find one.
Why this is harder than it used to be
Two years ago, deepfakes had tells: blurry edges around the hairline, unnatural blinking, mouths that didn't quite sync with audio. Those artifacts are largely gone. Today's AI video generation models are trained on millions of hours of real footage, and they've learned to mimic the micro-movements, lighting variations, and vocal cadences that make a person look real.
What hasn't changed is that AI-generated video leaves traces — just not ones the human eye can catch reliably. Detection now happens at the signal level, not the surface level.
What your eyes can still catch
Manual inspection won't catch everything, but it's worth doing before anything else.
Lighting inconsistencies
Does the light on the person's face match the environment? AI models sometimes struggle with moving light sources — watch for shadows that don't shift when the person moves their head.
Unnatural eye movement
Real people blink irregularly and their gaze drifts. AI-generated faces tend to blink at regular intervals and maintain unnaturally steady eye contact.
Teeth and hands
Still weak points for generative models. Teeth sometimes blur together mid-sentence. Hands may have extra or missing fingers, or joints that bend the wrong way.
Background drift
Look at objects directly behind the person's head. In lower-quality deepfakes, the background can blur, warp, or flicker as the model renders hair and edges frame by frame.
One more: play the video at 0.5× speed and watch whether lip movements match the audio precisely. A slight delay — even half a frame — can indicate a synthetic voice layered over generated or manipulated video.
These signs are useful but not conclusive. A well-made deepfake will pass every one of these checks. For anything that matters, you need a second method.
The reliable method: AI detection tools
Your eyes are looking at the surface. Detection tools look underneath it — analysing compression artifacts, temporal inconsistencies between frames, and statistical patterns in pixel distributions that generative models leave behind even when the output looks perfect to a human viewer.
UncovAI's video scanner runs this analysis automatically. Upload any video — a clip from a call recording, a social media post, a news segment — and it returns a confidence score with a breakdown of which signals triggered the result. It takes under 30 seconds and the first scan is free, no account needed.
Scan a video now →If you're checking videos regularly — for a business, a newsroom, or personal safety — creating a free account saves your scan history so you can track and compare results over time.
How AI video detection actually works
Detection tools don't compare a video against a database of known fakes. Instead, they look for statistical signatures that are intrinsic to how AI-generated video is produced.
Temporal coherence analysis examines whether the content of each frame is physically consistent with the frames before and after it. Real video cameras capture motion as a continuous physical process. Generative models produce each frame semi-independently, and the transitions between them carry subtle inconsistencies — particularly in fast movement and fine detail like hair or fabric.
Compression artifact analysis looks at how the video has been encoded. Authentic video compressed with standard codecs leaves characteristic patterns. AI-generated video, even after compression, retains different artifact structures because the original signal was generated rather than captured.
Facial geometry consistency tracks the spatial relationships between facial landmarks across frames. Real faces maintain consistent geometry because they're physical structures. Generated faces sometimes drift — tiny shifts in the distance between eyes, or the position of ears — that accumulate across a longer clip.
No single signal is definitive. Detection tools combine dozens of these signals and weight them against each other to produce a probability score.
A note on confidence scores
Detection tools give you a probability, not a verdict. A 94% confidence that a video is AI-generated is strong evidence — it isn't proof. Conversely, a 30% score doesn't mean the video is genuine; it means the tool didn't find enough signal to flag it.
Use the score as one input among several. If a video scores high and also has contextual red flags — an unsolicited message, an unusual financial request, a public figure saying something out of character — treat the combination seriously.
What to do if you find a deepfake
Don't share it. Forwarding a deepfake — even to warn people — spreads it further and can cause harm to the person being impersonated.
Preserve the evidence. Before reporting, save the original URL, take screenshots with timestamps, and if possible download the video file. Platforms often remove flagged content quickly, which can make it harder to investigate later.
Report it to the platform. Every major platform has a mechanism for reporting synthetic or manipulated media. Use the specific category — "manipulated media" or "AI-generated content" — rather than a generic report, as these are routed to different review teams.
Report to authorities if relevant. If the deepfake is being used in a scam or fraud attempt, report it to your national cybercrime unit. In the EU, contact your national CERT. In the US, the FBI's IC3 handles this category of fraud. UncovAI's AI scam and deepfake detector can help you document what you've found before filing a report.
Warn the person being impersonated. If a public figure or private individual is being faked, notify them directly if possible. They may not know it exists, and they have legal standing to pursue takedowns that you don't.
How to stay ahead of it
The technology evolves faster than manual detection skills can keep up with. The practical approach is to build a habit around tool-assisted verification for any video that involves money, identity, or urgent requests — the three categories where deepfake fraud concentrates.
If you receive a video call from someone asking you to act urgently on something financial or sensitive, verify the request through a second channel before doing anything. Call the person back on a known number. Send a message to an address you already have. For teams that need protection during live calls, real-time deepfake detection for meetings runs continuously in the background without interrupting the conversation.
The extra thirty seconds is the entire defence.
The short version
You can catch some deepfakes by eye, but not reliably. The tells that used to exist — blurry hairlines, bad lip sync, stiff blinking — are mostly gone in current-generation AI video. What remains detectable is the signal-level signature of generated content, which requires a detection tool to find.
If you have a video you're unsure about, run it through UncovAI. First scan is free, takes 30 seconds, and gives you a confidence score with a plain-language explanation of what was found. Trust your instincts — if something feels off, check it.
Scan a video free →Last updated June 2026. Detection capabilities and the state of generative video technology both evolve rapidly — check back for updates.