AI as a Cultural Translator: Bridging Localization Gaps in Global Campaigns

One of the biggest challenges growing brands face as they enter new markets is localization. A campaign that works in one country is unlikely to work in another – and not just because different languages are used. 

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Localization is about adapting content so that it still conveys the same meaning and conjures up similar emotions for a region-specific audience. A slogan that sounds clever in English could become meaningless (or even offensive) in German. An image that seems aspirational in the U.S. might come across as out of touch in Japan. These small details – colors, humor, tone – play a big role in how a brand is received in local markets. 

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In the past, businesses would hire human translators and regional marketing teams to create localized assets at scale. But while this approach is effective, it’s also an expensive and relatively slow way to handle localization. 

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This might all be about to change thanks to artificial intelligence (AI). Especially if brands can use it as a cultural translator, adapting their tone, imagery, and messaging to resonate with local markets. 

But how far can AI really go in bridging localization gaps? And where does human oversight fit in?

Let’s take a look at the challenges with using AI to localize content, brands that are doing it successfully already, and how to strike the right balance between AI and human expertise.

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The complexity of localization 

Cultural sensitivity is extremely important when localizing global campaigns and content. If a brand wants to stand out in new markets, build consumer trust, and grow a loyal customer base, it has to be hyper-aware of the local humor, values, and cultural undertones.

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When it isn’t, localization mishaps are much more likely. Slogans don’t translate well, imagery feels off, and the tone falls flat.

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For example, US-based Parker Pen Company used the slogan ‘It won’t leak in your pocket and embarrass you,’ in Spanish-speaking countries. Only ‘embarazada’ doesn’t translate to ‘embarassed’. It translates to ‘pregnant’. The slogan sounded something like this: ‘To avoid pregnancy use, a Parker pen’.

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In another localization mishap, nappy brand Pampers brought its product to Japan with stork imagery emblazoned across the packaging. The only issue with the seemingly ‘universal’ myth that storks deliver babies is that it’s actually a Western belief. This led to confusion and a disconnect between the brand and its target audience.

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How AI can assist with localization

AI can help brands avoid mistakes like this. Its strength goes beyond translation, ensuring content resonates culturally, emotionally, and contextually in every market.

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Take sentiment, for example. AI-powered sentiment analysis can detect differences in tone between, say, Japanese and English, softening bold messaging (that resonates with a British audience) so that it doesn’t come across as aggressive to a Japanese audience. 

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Then there’s context. AI can assist with editing and optimizing copy to better align with local behaviors and expectations. For example, an e-commerce brand can use it to tailor product descriptions according to what matters most to shoppers in each region. For customers in South Korea, that could be hydration and brightening. In Germany, that could be natural ingredients and sustainability. 

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AI is also transforming visual localization. Different cultures associate colors, symbols, and imagery with different meanings. Red is lucky in China but can signify danger in South Africa. A cozy winter campaign featuring snow-covered streets might work in Canada but feel completely irrelevant in Brazil. AI helps brands adapt visuals dynamically, suggesting culturally appropriate images while maintaining brand consistency.

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This ability to automate nuanced localization at scale is why AI has become essential for global brands. But while AI can speed up the process, human oversight is still required to ensure authenticity and emotional connection. That’s why the most successful brands take a hybrid AI-human approach.

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Brands successfully using AI for localization

Before we explore the balance of AI and human oversight, first let’s look at some brands using AI-powered localization successfully to connect with customers around the world.

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These companies have overcome the challenge of staying consistent while still feeling relevant to local audiences. Here’s how AI is helping to bridge that gap.

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L’Oréal: Scaling Personalized Beauty Content Across 37 Brands

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With 37 brands operating in more than 150 countries, L’Oréal is no stranger to the need for localization. To keep up with demand, the beauty brand built CREAITECH, its in-house AI-powered Beauty Content Lab that will create brand-aligned, region-specific content at scale.

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It will do this by training GenAI to “recognize the unique visual codes of our brands and launch innovative beauty campaigns faster,” according to Asmita Dubey, Chief Digital and Marketing Officer, L’OréalGroupe. Dubey added that L’Oréal will not use AI-generated life-like images of the face, body, hair, and skin to support or enhance product benefits in external communications. La Roche-Posay and Kérastase are the first brands in the group to use CREAITECH in their content creation process.

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More recently, L’Oréal Japan announced a partnership with Rakuten (a leading Japanese technology conglomerate with expertise in e-commerce, AI, and digital services.) to offer highly personalized beauty solutions to more than 100 million consumers in Japan. This collaboration aims to “revolutionize the beauty experience, providing customers with personalized, ideal beauty solutions for all.’

By using AI to scale creativity without losing authenticity, L’Oréal ensures its marketing feels genuinely localized, not just translated.

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Netflix: Mastering Cultural Adaptation in Entertainment

Netflix’s global success relies on more than translating subtitles. Thanks to AI, the company can adapt content for different audiences and cultures in the following ways:

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• Localized thumbnails – AI analyzes regional viewing preferences and dynamically adjusts cover images. A show might emphasize its romantic storyline in Japan but highlight action sequences in the US
• Title and synopsis adaptation – AI ensures descriptions align with cultural nuances, avoiding awkward direct translations
• Predictive recommendations – AI refines Netflix’s algorithm based on regional watch patterns, making sure users see content that feels locally relevant
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By adapting not just language but presentation, Netflix ensures global content feels tailored to every audience.

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Zendesk: Scaling Multilingual Customer Support

Localization isn’t just necessary for sales materials and marketing campaigns. It’s also an essential ingredient in accessible and high-quality customer service. This is how Zendesk, a leading customer service solution, uses an AI-driven translation platform, Phrase, to maintain excellent support across multiple markets: 

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• It instantly translates customer support tickets, help center articles and live chats
• It maintains accuracy and cultural relevance in responses
• It detects global support trends to improve service for different regions

For Zendesk, AI localization isn’t just about language – it’s about ensuring every customer interaction feels natural and culturally aligned.

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Why human oversight is still very necessary

While AI is a game-changer for brands in need of localization, it’s not a silver bullet. Sure, AI is fast, scalable and cost-effective compared to human translators. But at the moment, it doesn’t have the emotional intelligence or cultural intuition that comes so naturally to humans. 

That’s why a balance of AI and human oversight is key to bridging localization gaps. AI-powered localization tools can:

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• Automate translations at scale, instantly converting content into multiple languages
• Adapt messaging for different markets, adjusting phrasing based on local sentiment and tone
• Analyze regional trends, detecting commonly used phrases, slang, and industry-specific terminology
• Adjust visuals and formatting, ensuring images, colors, and design elements fit cultural expectations
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High-volume localization can be achieved quickly and consistently by AI. But it has its limitations.

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Where Humans Are Essential

There are a few areas where human oversight is essential. 

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• Humor and tone – While AI tools are getting better at detecting things like sarcasm, it still struggles with nuance. A joke that works brilliantly in one country might offend in another
• Cultural differences – AI can’t always detect when certain phrases or visuals might have unintended connotations
• Emotional connection – AI can analyze sentiment, but it doesn’t feel it. A local expert can ensure content resonates on a human level

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This is why a combination of AI and human oversight is key. AI can create localized content at volume – with linguists, content strategists, or cultural consultants then reviewing and refining to ensure the content is as authentic (and culturally accurate) as possible. 

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The Best of Both Worlds: AI and Human Collaboration

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L’Oréal and Netflix are prime examples of brands striking this balance. For L’Oréal, its CREAITECH lab uses AI to scale content creation, but marketing teams to fine tune messaging to align with brand values. 

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As for Netflix, look at this recent job listing it posted:

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“We are looking for an experienced Research Scientist with established track records in Multimodal LLM research areas to develop algorithms that power high quality localization at scale. In this rare opportunity, you will have the chance to conduct cutting-edge Machine Learning research to help enhance localization and global entertainment at Netflix.”

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The media company has relied on captioning, dubbing and UI localization for years – and now it looks as though it will supercharge these efforts through a combination of AI and human oversight.

How Wedia Helps Brands Scale Localization with AI

There are a few ways that Wedia’s Digital Asset Management system can support brands with effective localized campaigns. 

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One key enabler is multilingual metadata tagging. Traditionally, metadata tagging has been a time-consuming, manual task, requiring users to tag each asset individually. This process can be tricky and prone to mistakes, like inconsistencies in the language used. Integrated with DeepL, Wedia automates the translation of recurring terms in real time, making it easier for teams to find and repurpose content in their preferred language. 

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But Wedia doesn’t stop there. It integrates a cutting-edge Generative AI module into their DAM solution, which redefines how brands approach creative production at scale. Industry leaders like Bayer already leverage this innovation to streamline and enhance their visual content workflows.

In Bayer's case, users within the DAM can dynamically generate localized images by selecting age, ethnicity, or gender—automatically replacing the original person in an image with a fully AI-generated one, tailored to their target market, all while maintaining the integrity of the original visual composition.

This not only accelerates the creative process, but also ensures that content remains culturally and contextually relevant across diverse markets. The result is a combination of automation and personalization that enables instant, cost-effective visual localization at scale, while safeguarding brand consistency and compliance.

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In addition, Wedia’s integration with Claude AI enables the generation of image metadata and descriptions in over 20 languages, making content adaptation more agile than ever.

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Lastly, the Distributed Marketing module allows teams to access a huge range of options for producing and localizing marketing materials. They can be customized based on centrally supplied templates in various dimensions, versions, or with different content. 

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Ready to explore how AI can localize your brand at scale? 

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Want to scale your localization efforts with AI-driven tools? Book a demo with Wedia today.

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Not sure which DAM solution is right for you? Take our 3-minute self-assessment, it will help you choose a DAM system that truly meets the needs of your content ecosystem.

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