AI video is now a real market, and it's full of opportunities

AI video is hot right now, and the money is going to the tools people actually pay for.

We've found a lot of interesting signals. OpenAI announced in March 2026 it would shut down Sora, ending a planned $1B investment from Disney. Meanwhile, Kling raised $2.8B at a roughly $18B valuation, reporting about $500M in yearly recurring revenue. Video AI can attract huge attention, but paying users matter more than hype.

In this section, we look at who really pays for AI video today, from marketers and training teams to studios, and what the end of Sora means for the startups still chasing consumers.

Video has always been slow and expensive to make. A short ad can mean weeks of work, a shoot, a crew, and several rounds of edits.

We compare AI video tools, from avatar and ad creators to video models and dubbing. Then we rank what marketers, sellers and studios need most, and which problems are serious enough to pay to solve.

It shows you where a new tool can still win a budget, even with free generators one click away.

Monthly plans, credit packs, pay-per-second APIs, enterprise seats, per-video pricing for agencies, and licensing deals with studios: AI video companies make money in many ways.

We compare monthly plans, video credits and software sold to businesses. Video generation can be expensive for heavy users, while repeat business customers may bring steadier revenue than one-off creators.

You'll see where margins hold and where compute eats them, so you don't build or back a tool that sells more videos and earns less on each one.

Growth forecasts for AI video are easy to find. The reasons behind them are not. Here, we explain what actually pushes this market forward.

Some drivers are easy to see: brands need far more video for social feeds, models keep getting cheaper and better, and every platform pushes short-form video. Others are quieter, like companies translating one video into dozens of languages, online shops that need a clip for every product, and AI presenters replacing filmed training. Several of these feed one another.

Before building or investing, you should know what makes a business replace filmed video with generated video, and keep doing it after the first test.

Google's Veo and Synthesia come up first in most conversations about AI video, but the market goes well beyond them.

Many of the most interesting players are narrow. Some turn one product photo into dozens of ads. Others dub a video into another language with matching lips, or let a sales rep's avatar send a personal video to every lead. They rarely trend online, but they sell to businesses that pay every month.

Why are they hard to compare? A model maker, an avatar platform and an ad tool can all say they 'make AI video'. They sell to different buyers, at different prices, and many run on someone else's model, so it isn't always clear who owns the technology.

Below, you'll find the market grids and ecosystem maps we built to show who does what, from the models to the apps, and where new players keep showing up.

HeyGen, Higgsfield, Synthesia… a few AI video companies have built real revenue, mostly by selling to businesses.

HeyGen makes training and sales videos in different languages. Higgsfield serves social media marketers. Synthesia sells AI presenters for workplace training. Computing is still expensive, and strong sales don't yet prove lasting margins.

We'll look at how these teams chose one job that businesses already paid for, made video cheaper and faster to deliver, and kept customers once the novelty wore off.