A lot about video can be hard. The script, the visuals, the voiceovers, getting approvals. Also, getting approvals. Honestly, that last is sometimes the hardest.
Now AI is making a lot of it easier. If you’re using an AI video agent like Lucas (though there’s not anyone really like Lucas), then you have AI writing the script, handling the storyboard, animation, voiceover, transitions… pretty much everything.
But then somebody says they need it in Spanish, French, Japanese, Hindi and Arabic. Could you do that by next week?
Before the advent of AI, that question kicked off a mountain of work: script translations, new voice actors, edits, lip sync fixes, then all the format tweaks for different platforms. Just like magic, AI video localization turns what could take weeks into minutes. Instead of rebuilding the video for every target language, you keep the original video and let AI generate a localized version in any language you need.
The use cases where this saves real time keep expanding. Think training videos, sales outreach, ads, recap campaigns, customer onboarding and more. Anywhere you’d normally cap your reach at English (and maybe 1-2 other languages) is suddenly back in play. Here’s what that looks like in practice and where the workflow still needs a human in the loop.
Localization Used To Be the Bottleneck
Giving your customer or employee a video in the language they know best is naturally the gold standard. It’s not always possible when you have millions of customers, but AI is increasingly making this an achievable goal.
Perhaps unsurprisingly, most consumers (89% according to the latest research) say they prefer videos in their own language.
So how do you do that?
It wasn’t always easy. The old localization workflow was a series of handoffs. The script went to a translation vendor. The translated script went to voice actors in each target language. The new audio went back to editors, who’d lay it over the original audio and either accept the mismatch with the speaker’s voice and mouth movements or rebuild the scenes from scratch. Subtitle generation was its own track entirely.
Every handoff added time, cost and the risk of human error. The result was that most teams localized a video file into 2-3 languages and called it global content. The other markets got subtitles or nothing.
The right AI-powered localization tool collapses those handoffs into a single workflow. Drop the original video in, pick the target languages, get a localized video out. This generally involves LLM-powered video translation, then AI voice generation and finally subtitle generation. What’s new is that each piece comes from the same source so everything stays in sync.
The Stack Inside a Localized Video
A localized video isn’t one thing. It’s a stack of layered changes that are integrated into the final video. Of course, AI does all this behind the scenes, so you don’t need to worry about every step, but knowing about it helps you understand what’s going on under the hood.
Video Translation
The script gets translated into the target language. Advanced AI handles this well now for most major languages, but cultural context is key.
It’s important to consider idioms, regional slang, relevant units of measurement (fun fact: a gallon in London is larger than one in New York), currency exchange rates, even the order you list features. Depending on the cultural context, it can be helpful to have a human reviewer step in, especially for new markets.
AI Voiceovers and Voice Cloning
Once the script is translated, AI generates the voiceover in the target language. You can use a generic AI voice from a library, or you can use voice cloning to recreate the speaker’s voice in a different language entirely.
That’s what we did here. You don’t know Alfred, but if you did, you’d swear this was him speaking. But really it’s an AI clone of his voice.
The second option keeps the original speaker recognizable — useful when your CEO records a message you want to ship to 20 markets or when a sales rep records outreach that should sound like them in every customer’s native language.
AI Dubbing and Lip Sync
This used to be impossible without reshooting. AI dubbing aligns the new audio to the original video’s pacing, and lip-sync models reshape the speaker’s lip movements to match the target language.
The best ones handle edge cases like pauses, laughter and emphasis without sounding flat. When it works, the viewer doesn’t notice it’s dubbed. When it doesn’t, the mouth movements drift and the whole thing falls into the uncanny valley. You don’t want that.
Of course, if you’re using an AI avatar in the first place, you don’t need any dubbing. Whether it’s animated or photorealistic, the avatar updates to speak the new script flawlessly.
Subtitles
Subtitle generation is the easiest. In fact, we’ve been doing this for years without AI.
Most tools produce accurate subtitles in the target language as a fallback or accessibility option. Some platforms also support burned-in subtitles, especially helpful for short-form videos like those you see on social media. This is worth doing on every localized video even when the voiceover has been translated since many of your viewers will watch with the sound off.
Here’s an AI-generated video our AI video agent, Lucas, built from a short text prompt. Like many of his fellow AI agents, Lucas speaks dozens of languages, so translating our holiday greeting from English to French was a cinch.
Where Localized Video Pays Off
Not every video needs to be localized, but there are a few use cases that are particularly relevant. These are the ones we see most commonly with AI localization.
Training Videos and L&D
Training videos for global teams are an obvious one.
Localizing onboarding, compliance and skills content into employees’ native language drives completion rates and comprehension. Most L&D teams can’t afford to rebuild a 40-video curriculum in 12 languages from scratch. AI video localization makes it possible, and it keeps ongoing content creation sustainable as your library grows.
Sales and Outreach
Personalized sales videos sent in the prospect’s native language are much more, well, personal than ones sent in English with auto-translated captions.
With voice cloning, a single sales rep can ship outreach that sounds like them in any market and reach a wider audience without support from an internal video team.
Customer Communications
Onboarding, billing explainers, product updates — think of anything you’d send a customer that explains something complex. Spoken communication in someone’s native language reads as care, making this an opportunity to reduce churn and make your customer feel valued.
Social Media and Ads
Video ads, including videos for social, benefit from localization in a way that often directly affects your bottom line.
Different formats, different lengths, different visual treatments per platform, all multiplied by every target language can make for a massive volume of ads. Now you can translate every ad you’re testing (or even test translations) so it can be understood in any market you need to reach.
What To Look For in an AI Video Localization Tool
A few things worth checking before you pick a tool.
Translation quality across your actual target languages. The big ones (Spanish, French, German, Japanese, Chinese) are well covered. Smaller markets like Hindi, Arabic or Korean vary by vendor. Test with real scripts from your actual video content, not the vendor’s demo.
Voice options that match your brand. Some platforms ship with a library of AI voices. Others support custom voice cloning so the same person can speak in any language. If your videos lean on a specific presenter, voice cloning matters more than library size..
A workflow that connects to the rest of the video work. This is the one most teams overlook. If your localization tool lives in a different app from the tool that made the original video, every change to the original requires a re-export, a re-upload and a re-render. The way to ship localized video at real scale is to run localization as part of the same workflow you use to make the video: same prompt, same data layer, same edits, multiple languages out.
Real-time options for short-form content. For social media and ads you’ll iterate on quickly, you want a tool that can produce a localized video in minutes, not hours. Real-time rendering matters for the use cases where speed is the point.
API access if you’re scaling. Localizing one video is a UI task. Localizing a million Personalized Videos for every customer in a CRM is an API task. If your roadmap includes the latter, make sure the API can deliver localized output at volume. Look for a platform where you can set up your video in each target language upfront, then call any version via API alongside the rest of your personalization data. Make sure it handles fonts correctly across languages too — scripts like Arabic, Chinese and Hindi need different character sets, and your video should render cleanly in every one you target.
High-quality output across all of the above. AI video localization is only useful if the result looks good enough to ship. And confirm that your video will be truly brand, including brand voice and animation style, not just matching fonts and colors.
One Workflow for Every Language
For most AI tools, localization isn’t a separate capability you add onto your video workflow. It’s a feature of the tool itself. That’s certainly the case with our own Lucas AI Video Agent, where you can generate the original video, edit it, personalize it and then ship it in 50+ target languages all in one place. That includes subtitles, on-screen text, voiceover — the works.
We’re not the only AI video tool that can do translation. But we are the only one that can do it at scale in real time, personalizing videos for thousands, even millions of viewers.
However you choose to localize, our message is — do it! Just a few clicks can take a video from a single source language to global reach. It increases accessibility and shows personal attention (which we’re all about), and it really is easy. Basically, magic.
Curious how Lucas can help you localize and upgrade your video content? Let’s chat.
