Text-to-Video
Text-to-Video
What is text-to-video?
- AI that generates video from text alone
- Diffusion extended along the time axis (motion and consistency are the key challenges)
- Sharply cuts the cost of producing ads, training, and short-form video
What text-to-video really changes is the production sequence. Before, you wrote a proposal, got budget approval, and scheduled a shoot before seeing a single frame; now you make drafts first and start the meeting with them. Where a marketing director once had to persuade people by saying 'this is the feel we want,' there are now three 15-second candidate videos on screen. The biggest change is the ability to produce cuts you can discard without regret in volume.
Uses fall into three broad types: pure text-to-video, which builds a scene from a sentence alone; image-to-video, which takes a single product photo and adds only motion; and video-to-video, which changes only the mood of footage you have already shot. In practice, the approach with the fewest failures is image-to-video anchored on a real product photo. Most commercial tools generate 5–10 seconds at a time, so a 30-second video is built by stitching together three or four cuts. The purpose differs from AI avatar services, which composite a face to read a script, so be sure to distinguish between tools that create scenes and tools that create a speaking person when you place an order.
The cost structure is different too. Most tools charge by credits, so a single 5-second clip costs from a few hundred to a few thousand won, but getting one usable cut usually takes five to ten re-runs. The real cost comes not from generation fees but from the time of the person who rewrites prompts and picks the best result. Work that once cost several million won per outsourced video shrinks to a day’s effort, but unless you decide in advance who will spend that day, you end up with a paid tool that nobody touches.
The expectation that breaks most often in the field is that 'one line of prompt gives you a finished video.' In reality, the model’s face and clothing color change from cut to cut, and Korean captions placed inside the frame come out with smeared characters. It is safer to add text during editing rather than leaving it to the video itself. Even riskier is using AI to depict a product that is actually on sale. If the handle shape or number of buttons differs from the real item, it can turn into a false-advertising problem, so set the principle in advance that videos attached to a sales page mix in footage of the real product.
John KimInstructor John Kim, author of "B2B Marketing Design" and CEO of Nanum Consulting
Seungtae ParkAX instructor who teaches by building AI business development and marketing automation himselfIt began with research on extending image-generation diffusion models along the time axis, and public interest exploded in 2024 when high-quality video generation models were released.
Consider a hypothetical case: Company A, which sells home appliances online and has 260 employees. It needed to post three short-form videos a week to its own store, but outsourced production cost KRW 1.8 million (≈ US$1,350) per video and draft approval took two weeks, so videos were late for every new-product launch. In the end, four people on the marketing team decided to try making them in-house.
- When Kim, a manager on an e-commerce team, reviewed the past six months of 27 short-form videos, every top-viewed cut turned out to be a product close-up, yet KRW 600,000 (≈ US$450) per video was going to producing background shots alone.
- Following the conclusion to 'let AI handle only the backgrounds,' the assistant manager in charge fed in product photos and generated 5-second clips with image-to-video. In the first week, 40 runs yielded just six usable cuts.
- After the same model’s face kept changing from cut to cut, the team wrote a division-of-roles rule into an internal document: scenes with people use existing footage, and AI handles only objects and backgrounds.
- Legal review objected that 'a handle that differs from the real product can’t be used,' so cuts where the product fills the frame now use live-action footage only, and the team added a step in which the team lead gives final approval to any video for a sales page.
- Three months later, production cost per video fell from KRW 1.8 million (≈ US$1,350) to KRW 520,000 (≈ US$390), the time from planning to upload dropped from two weeks to three days, and short-form output rose from three videos a week to seven.