Successful localization starts with GenAI

Successful businesses are localizing everything from payments to content

In the digital world, many businesses are adopting forms of localization that make it possible for them to adapt to how they cater to audiences virtually. For instance, Airbnb excels at localization by translating its website into 62 languages and customizing features like payment methods (e.g., Alipay in China) and login options (e.g., WeChat integration) for specific regions.

Similarly, ASOS adapts its ecommerce platform to reflect region-specific changes in currency, size guides, and even fashion trends. These adaptations help create a familiar shopping environment for customers worldwide, one that feels like it’s been made just for them.

Netflix is a master of localization through personalization. Netflix personalizes its interface for users in different regions by tailoring content recommendations and even modifying movie posters based on local tastes. This level of customization helps ensure that its content resonates with global audiences.

Localization can also involve technical adjustments like adapting date formats (e.g., DD/MM/YYYY in Europe vs. MM/DD/YYYY in the U.S.), currencies, and units of measurement. For example, Square customizes its payment processing platform for different countries by aligning with local laws, currencies, and even receipt designs.

As impressive as those examples are, localization is becoming even more sophisticated thanks to AI.

GenAI is future of localization

GenAI is changing the localization industry by automating processes, improving accuracy, and enabling scalability. In 2025, AI-driven technologies like neural machine translation (NMT), natural language processing (NLP), and hyper automation are becoming inseparable from successful localization strategies.

One of the most significant impacts of AI is its ability to deliver high-quality translations at scale. Modern large language models (LLMs) provide context-aware translations that sound natural. They continuously learn from user feedback to improve accuracy over time. For instance, AI enables Netflix to generate subtitles and dubbing in multiple languages while maintaining cultural relevance.

AI also enhances multimedia localization by adapting images, videos, and audio for different markets. Meta’s AI tools can translate text embedded in images while preserving font styles and design elements. AI-powered platforms like Weglot automate content detection on websites, which helps ensure that all elements requiring localization are identified without manual effort.

Have you ever wondered how companies like Spotify and Amazon can deliver highly localized experiences? They’re using AI for hyper-personalization. Analyzing user behavior and preferences across regions makes it possible for AI to tailor content recommendations, marketing messages, and even user interfaces to individual tastes. This capability is the key to delivering highly localized experiences that drive engagement and loyalty.

AI also streamlines quality assurance (QA) processes by automatically detecting errors or inconsistencies in translations. Translation and localization platforms perform AI-driven linguistic checks early in the localization lifecycle to deliver high-quality output before human reviewers step in. This ability reduces costs and accelerates time-to-market for localized content.

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Success with localization means mastering critical success factors

Achieving successful localization online requires a strategic application of AI, cross-departmental collaboration, and cultural sensitivity. The following are critical factors that contribute to effective localization.

Have a clear strategy aligned with business goals

Integrate localization into the broader business strategy rather than treat it as an afterthought. For example, identify target markets through thorough research and prioritize regions based on potential ROI. Set measurable goals—such as increasing market share or improving customer satisfaction—to align localization efforts and overall business objectives.

Ensure your AI-driven tools have access to high-quality data

Preparing your AI models to localize content means training them with high-quality data to bring about accurate, culturally sensitive, and unbiased outcomes. For instance, deploying multilingual GenAI to support applications like chatbots requires data that reflects the nuances of different languages, dialects, and cultural contexts.

Achieving this level of precision necessitates sourcing highly skilled subject matter experts who can provide linguistically and culturally relevant input. Subject matter experts help fine-tune a GenAI model with diverse datasets that account for regional variations, idiomatic expressions, and cultural preferences, minimizing the risk of inaccuracies or unintended bias.

Additionally, you need continuous monitoring and iterative training to refine the model as languages evolve and audience needs change. High-quality training not only enhances the AI’s ability to localize effectively but also fosters trust and engagement with global audiences.

Embed AI throughout the entire localization process

AI can improve just about every aspect of localization—so don’t hesitate to use AI to support multiple tasks. For example, a localization team might apply AI for a variety of needs, including tone adaptation and grammar checks that enable you to create culturally relevant and polished content. You should consider using AI for transcreation, gender adaptation, and source content analysis, to help your teams ensure inclusivity and resonance with diverse audiences.

Because localization requires management of complex workflows, consider also tools like translation management system connectors or application programming interfaces to simplify workstreams. And QA tools and test reviews will help you effect high-quality results.

Combine human expertise with AI

While AI plays a crucial role in automating repetitive tasks and scaling localization efforts, human expertise remains indispensable for capturing cultural nuances. Translators and linguists provide the empathy and contextual understanding that machines lack.

For example, Airbnb’s success in China was partly due to its decision to rename itself “Aibiying,” a term that resonates culturally with Chinese audiences. Combining AI efficiency with human creativity balances both speed and quality in localization efforts.

Be culturally aware

Localization is about respecting cultural norms and preferences along with, yes, translation. Businesses must adapt visuals, humor, idioms, and even product offerings to align with local expectations. For instance, McDonald’s adjusts its menu items globally based on dietary restrictions and cultural preferences, such as offering vegetarian options in India.

Capitalize on multilingual SEO optimization

Localized websites must be optimized for local search engines by incorporating region-specific keywords and metadata. Doing so improves visibility in search results and drives organic traffic from target markets.

For instance, multilingual SEO strategies to cater to international audiences can help e-commerce companies enable sellers to translate product listings and target region-specific keywords. While this approach enhances discoverability, success depends on tailoring SEO efforts to the preferences and behaviors of each market.

Provide a seamless user experience

A well-localized website or app provides a seamless experience by adapting technical elements like navigation layouts, payment methods, date formats, and units of measurement to local standards. For example, if applicable, you might offer region-specific payment options such as cash-on-delivery in India or Alipay in China. Testing localized platforms before launch helps ensure functionality across all markets.

Measure success

Tracking key performance indicators (KPIs) such as website traffic from target regions, conversion rates, customer satisfaction scores (CSAT), and revenue growth helps you evaluate the effectiveness of your localization efforts. Advanced analytics powered by AI provide insights into user behavior across markets, enabling continuous optimization of localized content.

Practice agile, cross-functional collaboration

Localization involves multiple stakeholders—from developers and designers to marketers and linguists—working together closely. Proactive collaboration ensures that international considerations are integrated early into product development cycles rather than being addressed as last-minute fixes.

Consider a frontier AI data foundry platform

A frontier AI data foundry platform can help you manage the complex workflows necessary for effective localization. This type of platform combines AI-driven automation with customizable tools to streamline processes like terminology extraction, machine translation quality evaluation (MTQE), and source content analysis.

With a frontier AI data foundry platform, you can efficiently handle diverse localization requirements, such as adapting user interfaces, managing cultural nuances, and delivering consistent quality across multiple languages.

The bottom line is that a frontier AI data foundry platform helps you take control of the moving parts required to localize.

Discover how Centific’s frontier AI data foundry platform can help you.