AI video generation is the use of generative AI to create new video, or modify existing footage, from inputs such as text prompts, images, scripts or audio. It covers text-to-video generation, animating still images, talking-head avatars, AI editing tools and automatic dubbing. The field advanced rapidly from 2023 onwards, with several major labs releasing high-quality video models.
This page covers the whole field and its uses. For how a prompt becomes a video clip, see What is Text-to-Video?
Key takeaways
- AI video spans generation, editing, avatars and dubbing.
- Most leading generators use diffusion-based models, often diffusion transformers.
- Clips are typically short; long, consistent stories remain hard.
- Business use is growing in marketing, training and localisation.
- Deepfake risks make consent, labelling and provenance essential.
AI video generation explained in simple terms
Making a video normally means a script, a camera, actors, lights and hours of editing. AI video tools compress parts of this. You can describe a scene and get a short clip, turn a product photo into a moving shot, have a digital presenter read a script, or translate a video so the speaker appears to talk in another language. Each tool replaces a different step of traditional production.
Main types of AI video generation
| Type | Input | Output | Example use |
|---|---|---|---|
| Text-to-video | Prompt | New clip | Concept shots, social clips |
| Image-to-video | Still image plus prompt | Animated clip | Bringing product photos to life |
| Video-to-video | Existing video | Restyled or edited video | Change style, weather or background |
| AI avatars | Script (and a consented likeness) | Talking presenter video | Training and explainer videos |
| AI dubbing and lip-sync | Video plus translation | Translated video with matched lips | Localising content |
| AI editing | Raw footage | Cuts, captions, highlights | Turning long videos into short clips |
How it works, briefly
Video is a sequence of images that must stay consistent over time. Modern generators extend diffusion models to handle time as well as space, often splitting video into small space-time patches processed by a transformer. The model must keep objects, lighting and motion consistent across frames, which is much harder than generating a single image. Avatar and dubbing tools combine speech generation, face animation and lip-syncing models.
Business uses
- Short social and ad clips for testing creative ideas.
- Product demos and animated product shots.
- Training and onboarding videos with AI presenters.
- Localising videos into many languages.
- Repurposing webinars into short highlights.
- Storyboards and pre-visualisation for film and ads.
A worked example: localising a training course
A company has 20 English training videos for staff in India, Brazil and Germany.
- AI transcribes the audio (speech-to-text).
- The script is translated and checked by native speakers.
- AI dubbing generates voices in Hindi, Portuguese and German, matching the original speaker’s tone, with the speaker’s consent.
- Lip-sync adjusts the presenter’s mouth movements.
- A reviewer checks accuracy, pronunciation of product names and cultural fit.
Work that once needed studios and voice actors for each language can be done far faster, though quality review remains essential.
Current limitations
- Clips are usually short; long scenes often lose consistency.
- Physics, hands, text and fine motion can look wrong.
- Keeping the same character across shots is difficult.
- Precise control of camera, timing and action is limited.
- Generation can be slow and expensive.
Risks and responsible use
- Deepfakes: realistic fake videos of real people can defame, defraud or mislead voters. Always get consent to use a person’s likeness or voice.
- Disclosure: the EU AI Act requires deepfakes to be disclosed, and major platforms require labels for realistic synthetic video.
- Provenance: watermarking and content credentials, such as C2PA, help show how videos were made.
- Copyright: training data and output ownership questions remain unsettled.
See synthetic media for more on detection and provenance.