One tool to rule them all.
That’s the essence of agentic workflows. Like with a magic wand, these processes put AI agents to work and help you convert complex instructions into actionable steps. 🪄 All in one place, all in one go. Independently, responsively, and with a certain degree of flexibility.
Why should localizers care?
Because localization is no longer about replacing strings in UI. It’s about adapting visuals, tweaking brand messages, aligning user experience with the new culture, reshaping videos for the new audience, and keeping everything culturally on point. That’s a lot to take for one person. Sometimes, even a whole team of skilled experts can’t keep up with the demanding localization pace. Automation was the answer to this challenge for quite a long time. But this solution is slowly becoming “old-school”, giving space to the new approach that promises wonders: agentic workflows.
In this article, you’ll find out what agentic workflows are, why they’re different from your current automation stack, and how they can elevate localization across formats: text, images, audio, and video. I’ll test Genspark, an AI agent, to simulate typical localization workflows and evaluate if it’s a miraculous time saver or just a shiny addition that brings nothing to the table. 👀
🫥 Agentic w-what? 🔗
Agentic workflows are a new way of automating work using AI agents that can reason, act, and coordinate with each other. Unlike traditional workflow automation that uses macros or scripted flows, they don’t just perform tasks but make decisions along the way. Without constant human intervention.
To achieve this, agentic workflows rely on AI agents for problem-solving, deep reasoning, or data analysis. These tools can also choose and execute actions based on the input provided in the prompt. AI agents easily adapt to the context, which makes them a flexible and scalable solution for diverse tasks and industries.
For localization, this approach might be game-changing. Agents can prepare the content for localization, detect tone mismatches in subtitles, check if your UI breaks or flag culturally awkward visuals, and help with cross-channel localization. Independently and automatically. Instead of juggling five tools and ten tabs, you get a chain of coordinated agents working for you whenever you need them in one simple interface.
🧭 The multimodal maze 🔗
Text is only half the story. Localization also revolves around sound, images, videos, layouts, and cultural nuances expressed in every possible form. And yet, many of these elements are still handled in isolation.
That’s how you may end up with a perfectly translated UI that suddenly breaks when you implement the strings to the new language version. Or with creatively rendered subtitles for a promo video with a tone that does not match the brand style guide. Even worse: your website receives an update with new videos, images, and text, but every piece of content reads like teleported from another world: terminology varies, style is not consistent, and the user is left confused.
Sound, images, videos, and layouts are part of localization as much as text. Yet, many of these elements are still handled in isolation. AI agents can provide consistency for the whole package
Agents can connect the dots. Once you implement agentic workflows in localization processes, you can see how one tool adapts strings, another checks for consistency in subtitles, a third tweaks layout spacing, and a fourth ensures the visuals make cultural sense. When something changes along the way (for example, key terms on the website), agents can adjust other pieces of content automatically. That’s how multi-agent collaboration can help you avoid mismatched elements that confuse users and dilute brand messaging.
🦾 Genspark in action 🔗
How to put this agentic approach into action? Let’s take three scenarios and throw them into a powerful AI agent. I’ll go beyond agentic translation and use Genspark for the localization of visuals, subtitle generation, and UI layout modifications to see what the wins, limitations, and potential surprises are.
The test of the best 🔗
First things first: Genspark is one of the most powerful AI agents out there. It grabbed my attention from the start thanks to its easy access (no waitlist like Manus), intuitive interface (like ChatGPT), and quite impressive execution. I’ve tested it, it won me over, and it ticks all the boxes on my personal “Best of” list. 👌
That said, don’t just take my word for it. If you're exploring how to bring agentic power into your localization workflow, it’s worth experimenting with different tools to see what fits your needs best.
Most importantly, remember: adding AI agents doesn’t mean removing human oversight. As tempting as it is, don’t let agents run the show unsupervised. Humans still need to be there to ensure the content truly connects with your audience and avoids cultural blunders.
With that clarified, let’s get down to work.
🎙️ How ready is localization for AI workflows? Listen to our Bridging the Gap podcast episode with Julia Díez on the readiness gap for AI for our take.
Test 1: Image localization 🔗
📸 Five images, three cultures, one brand.
How can you ensure the visuals on your website are relevant for every market? And how do you avoid cultural missteps that could hurt your brand? The answer lies in image localization. Here's how we can use Genspark for it.
"I need to analyze these images for cultural appropriateness across different markets. Please help me identify potential issues and suggest adaptation strategies.
Target markets: Japan, Morocco, USA. Business objectives:
- Entering these new markets
- Building local trust and cultural respect
- Maintaining brand consistency where possible
For each image I upload:
- Identify any culturally sensitive elements
- Suggest specific adaptations for each target market
- Explain the cultural reasoning behind your recommendations
- Advise whether to create separate versions per market or use one adapted version
I'll upload the images in subsequent messages."
In the next step, Genspark was provided with five images: a woman drinking wine, a man jogging outdoors, a family sitting on a sofa, a couple lounging in the trunk of a car, and a simple product shot of a bottle resembling shampoo.
Within seconds, it generated a detailed analysis of each image, highlighting potential cultural sensitivities. It also offered thoughtful suggestions on how to adapt each visual to better align with different market expectations. Since the recommendations sounded reasonable, I then asked Genspark to put them into action and generate relevant images for 🇲🇦 Morocco and 🇯🇵 Japan. It came as no surprise that the original images were already appropriate for the US market and didn’t need any further tweaks.
Genspark chose Gemini Imagen 3 as a tool and teleported models to new locations, making sure the visuals resonated with the target cultures.
The results were decent. Instead of a blond woman with wine that was suitable for the US audience, the tool presented a Moroccan lady with mint tea, the jogging man was presented in Japanese and Moroccan settings, the bottle received new finishing touches, and the couple in the car was placed in a beautiful cherry blossom scenery. For the family on the sofa, Genspark employed another generative AI tool, Recraft, to show local interiors and ethnicity.
The entire process took less time than using one or several image generators separately, and the new creations were backed up with the reasoning behind the adaptations the agent chose to perform:
Unsurprisingly, Genspark makes decisions on the fly without constantly checking in with a human. It selects tools randomly to generate outputs, so if you have specific preferences or requirements (e.g., image generators, voices, or video styles), be sure to include them in your prompt. Also, don’t skip the review stage. Without proper guidance, AI-generated visuals can lean toward overly generic or traditional depictions.
This is what happened in the case of the Moroccan family watching TV: the image was culturally relevant, but perhaps too traditional for a modern brand, unless that’s exactly the tone the campaign aimed for. If your audience profile isn’t clearly defined in the prompt, agents may default to stereotypical representations. It's important to verify the output with your target market in mind, especially when visuals are involved.
Test 2: Transcription + subtitles + voice-over script 🔗
📹 After visuals, it’s time for videos.
In the second test, I used a short scene from a Polish movie and asked Genspark to transcribe it, create subtitles, and finally draft a script for voice-over.
The scene comes from the satire movie “Miś” from 1980, containing many political and cultural references that might easily get lost in translation.
"I need help with this Polish movie scene:
Please:
- Create a complete transcript of the spoken content
- Format this transcript into proper Polish subtitles with:
- Appropriate line breaks (max 42 characters per line)
- Timing suggestions for each subtitle segment
3. Adapt these subtitles for the US audience, considering:
- Cultural references that may need explanation
- Technical terms that require localization
- Space constraints of subtitles
4. Create a voice-over script for localization into US English that:
- Maintains the original meaning
- Adapts to natural speech patterns of the target language
- Includes pronunciation notes for challenging terms
- Adds voice direction notes (pace, tone, emphasis)
For any cultural references or idioms, please explain your adaptation choices."
Genspark clearly displayed its “thinking” process, walking through each step in a transparent way. It generated subtitles for the 35-second scene in no time. However, it didn’t catch the entire dialogue. Roughly the first 20 seconds of the video were missing from the analysis. That said, the portion Genspark did process was accurately transcribed and subtitled, with solid alignment between audio and text.
Since the first part of the video was skipped, the time codes in the subtitles were off. Some cultural nuances were also lost in the process, though the subtitles themselves were clear and easy to follow. Genspark’s biggest strength in this test was its detailed reasoning: it not only explained its choices but also generated a well-structured voice-over script. The cultural adaptation notes added valuable context and served as a solid foundation for voice-over actors.
While the subtitles weren’t incorrect, they would benefit from human review and a few minor tweaks. It’s also likely that Genspark would have captured the full dialogue if the video had been uploaded directly, rather than shared via a link. But apparently, that’s not possible yet.
When I asked Genspark to recreate the video with an English voice-over, it rejected the request, explaining:
“These activities could potentially infringe on copyright laws and the intellectual property rights of the original content creators. The clip from ‘Miś’ is copyrighted material owned by the film production company and/or distributors.”
Genspark was only willing to assist with non-copyrighted material, and even then, the video shouldn’t come from YouTube to comply with the platform’s terms of service. This shows that the agent can act not only intelligently but also responsibly, respecting legal and ethical boundaries when handling creative content.
Respecting the tool’s boundaries, I followed up with a request for a voice-over on my own educational, non-copyrighted video. However, this was also rejected, with the explanation:
“Unfortunately, I don't have the capability to directly create or modify video files with voice-overs, nor can I process video uploads through this chat interface.”
There’s no way to upload a video file. It’s clear that while Genspark shows promise, there’s still room for improvement, especially when it comes to video processing tasks.
Test 3: Localized UI layout tweaks 🔗
📲 The last test was all about UI.
In this scenario, I provided Genspark with three UI mockups (created first by ChatGPT via Genspark), asked the tool to analyze the screenshots, and show recommendations for all target languages.
"I need to localize this UI for several international markets. Analyze this interface screenshot and provide recommendations for the uploaded UI screenshots.
Target languages to consider:
- German (known for text expansion, ~30% longer than English)
- Arabic (right-to-left reading, different typographic needs)
- Japanese (different character set, potential vertical text)
- Polish (specialized characters, moderate text expansion)
Please provide:
- A detailed analysis of potential layout issues for each language, including:
- Elements likely to break due to text expansion/contraction
- Directional flow changes needed for RTL languages
- Typography adjustments required for different scripts
- Date/time/number format considerations
2. Specific recommendations for each identified issue, including:
- Layout modifications (with reasoning)
- Component redesign suggestions
- Flexible spacing strategies
- Responsive design approaches
3. A prioritized list of UI components that would need the most attention during localization.
4. Examples of how similar UI patterns could be adapted while maintaining usability and brand consistency.
Include visual descriptions or mockup suggestions where possible."
Genspark not only analyzed correctly how the layout may expand but also displayed code for layout modifications. It included suggestions such as implementing flexible containers that can grow with text expansion, implementing a base RTL framework for Arabic localization, or adding vertical text options. The tool also explained how to redesign certain components and implement responsive design approaches. The mockup suggestions were useful too, showing navigation bars or buttons in all four languages.
All in all, the UI layout analysis was in-depth and provided actionable recommendations that can help maintain usability and visual appeal in all target languages.
🧙♂️ The cost of magic solutions 🔗
Genspark is fast and efficient. It can serve as a powerful assistant in your localization workflows, but this magic comes at a cost. While image and video generation are impressive, they take more time and consume more credits. These operations are only available with the Plus subscription, which includes 10,000 credits per month. If you go beyond that, you’ll be looking at a costly upgrade to the Pro version. 🤑
Beyond time and budget, there’s another risk: the tool’s confident suggestions can make it easy to switch off your critical thinking. No matter how sophisticated agents become, human oversight should remain.
Using agents or LLMs for translation and localization might be tempting, but relying on machines alone is rarely a wise move, especially when cultural nuance is involved. AI agents can’t do everything. And even when they perform well, human expertise is still essential.
While fast and efficient, AI agents still need human oversight when used. Genspark can get pricey and, above all, make it easier for the user to switch off their critical thinking
Make sure it's people (localization professionals, cultural consultants, reviewers) who have the final say. At the very least, they should review the content for accuracy, hallucinations, omissions, bias, awkward phrasing, and potential cultural missteps. There’s no engagement without authenticity, so make sure your localized content respects, understands, and celebrates the cultural landscape of your target market, no matter what tools you use in your localization processes.
↪️ Takeaway 🔗
Agentic workflows already offer an extra pair of hands in modern multimedia localization. Tools like Genspark and Localazy (which can now be integrated with OpenAI using your own token) make it easier than ever to start experimenting. More agentic features are already in our pipeline, so what feels cutting-edge today may become your standard tomorrow.
Not sure where to begin? Start small. Try using an agent to adjust subtitle tone that matches your product voice or to suggest fixes for layout issues in a right-to-left UI. Once you see the value, you can scale up. Remember, however, that AI agents are not magic solutions to all your localization pains. Keep humans around for best results and authentic engagement.
