The AI Video Landscape
AI video tools generate short clips from text prompts, images or other videos. They are changing quickly: new models appear every few months, and capabilities, clip lengths and pricing shift with them.
Main approaches
| Approach | Input | Good for |
|---|---|---|
| Text-to-video | a written prompt | concept clips, B-roll, ideas |
| Image-to-video | a still image + motion prompt | animating product shots, illustrations, keyframes you control |
| Video-to-video | an existing clip + style prompt | restyling, effects |
| Avatar / talking-head | a script and an avatar | explainers, training videos |
Popular tools include Runway, Pika, Luma, Kling, Google's Veo models, OpenAI's Sora and avatar tools such as Synthesia and HeyGen. Check each tool's current features, clip limits and commercial terms.
Realistic expectations
- Clips are usually short (seconds, not minutes); longer videos are edited together from many clips.
- Physics, hands, text and complex interactions can glitch.
- Consistency of characters and products across shots is the hardest part.
- Generation costs credits per second of video; iteration adds up.
Where AI video works well
Social media content, ad variations, B-roll for explainers, product teasers built from still images, storyboards and pre-visualisation, and short loops for websites.
Where to be careful
Anything presented as real footage, real people's likenesses, news-like content and regulated advertising. Disclose AI use where platforms or laws require it.
Check yourself
- What is the difference between text-to-video and image-to-video?
- Why are longer AI videos built from many clips?
- Which uses require extra care?
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