AI-generated videos have become sophisticated enough to fool even careful viewers, with tools capable of producing photorealistic footage from a single text prompt. As deepfakes are increasingly used for misinformation, financial scams and impersonation of public figures, spotting synthetic video has become a basic digital literacy skill. From unnatural facial movements to inconsistent lighting and missing metadata, a combination of small visual and audio cues, along with a few verification habits, can help viewers tell real footage from fabricated content before they share it.
Watch the face and body movement
Faces remain one of the weakest points for AI video generators. Blinking that looks too fast, too slow, or oddly regular is a common tell, as are facial expressions that do not quite match the emotional tone of the scene. Skin, eyes and hair can also shift subtly in texture between frames despite depicting the same person throughout a clip. Body movement offers another clue, since AI-generated figures sometimes appear to glide rather than walk, with motion that looks unnaturally smooth and lacks the small corrective movements a real human body makes. A single odd expression may not mean much, but several such signs appearing together in one clip is a stronger indicator of synthetic footage.
Check the hands and background details
Hands continue to be one of the hardest elements for AI tools to render accurately. Extra or missing fingers, fingers bending at unrealistic angles, or hands appearing to pass through objects instead of gripping them are frequent giveaways. Background elements often carry the same distortions, including furniture that warps as the camera moves, patterns on clothing or walls that shift, or objects that briefly duplicate or blend together. Since these errors tend to surface at the edges of a frame rather than around the main subject, it helps to look away from the person's face and scan the corners of the scene and anything being held or touched.
Listen for mismatched audio and lip sync
Lip movements that fall out of sync with spoken words, particularly toward the end of a sentence, remain a classic sign of manipulated or synthetic video. Voice cloning has advanced to the point where tone and accent alone are no longer reliable indicators, so it is worth listening instead for a lack of natural breathing sounds, filler words, or pacing changes, since AI-generated speech often carries a flatter, more mechanical cadence than natural human speech. Background noise is another useful check, as real recordings typically pick up some ambient sound, while audio that sounds unusually clean or does not match the visible setting is worth a second listen.
Look closely at on-screen text
Any text appearing inside a video, whether on signage, subtitles, a shirt logo or a phone screen, offers a simple test, since AI video generators frequently produce text that is blurry, nonsensical or that subtly changes between frames. Pausing on a frame containing visible text and checking whether it remains legible and consistent from one moment to the next is one of the easiest checks a viewer can carry out without any specialised tools.
Notice inconsistencies in lighting and reflections
Real-world lighting follows predictable physical rules, with shadows falling in one direction based on the light source and reflections in mirrors, windows or glasses matching what is actually present in the scene. AI-generated video often struggles to maintain this consistency, producing shadows that point the wrong way, reflections that do not match the subject, or lighting that shifts illogically between cuts. These inconsistencies can be easy to miss at normal viewing speed but tend to stand out once a viewer knows to look for them.
Examine metadata where available
Video shot on an actual camera or phone typically carries metadata such as creation date, device model and camera settings. AI-generated videos frequently lack this information altogether, or carry metadata tied to generation software rather than a camera. This can be checked by viewing a downloaded file's properties, though metadata is easily stripped and is not accessible at all for video viewed only within an app or browser.
Verify beyond the visuals
Visual inspection alone is not always enough, particularly as generation tools continue to improve. Checking for a platform's AI disclosure label is one starting point, though the absence of a label is not proof a video is genuine, since labelling relies heavily on creators disclosing this information themselves. Running a reverse image search on keyframes from the clip, or checking whether credible news outlets are reporting the same event, can help confirm whether a dramatic video has any independent corroboration. AI detection tools such as those built by Hive, TrueMedia.org, Reality Defender and Sensity can offer an additional data point, though none are foolproof, and their accuracy drops on low-resolution or heavily compressed footage. Examining the account that posted the video, including its age, posting history and pattern of content, often reveals more about its credibility than the footage itself.
