How Agentic AI is Changing Localization

Agentic AI in AI Localization

Localization makes content accessible and relevant to people across cultures and countries. It’s about translation, but also a message’s essence and context. Traditionally, this has been a manual, meticulous process, requiring deep knowledge of both the language and culture of the source and target environments. Initially, only humans could do this. Then, machine translation and prompt-and-response AI originated the current paradigm of Machine Translation (MT) + Automated Post Editing. Next is Agentic AI.

Move 37

In AI circles, “Move 37” is a legendary event. It is one of the foundation myths of the whole AI movement. In Eastern cultures, the strategy game “Go” is a staple for anyone in business. More complex than chess, it is won via long-game tactics. Long after computers outsmarted the world’s best chess masters, “Go” remained a last frontier for AI. That was until 2012, when the AlphaGo AI system completed move 37. Initially, this seemed like an odd move that humans didn’t understand. However, as the game unfolded, onlookers realized the AI had become creative and devised a new strategy — one that no human player had thought of before. AlphaGo has only lost one game against human players since that event. AlphaGo was trained on data (expert Go players) and given a goal (win). It achieved its goal in a novel way that dumbfounded the people who had trained it. Why is this relevant? It means that AI systems had started becoming creative in ways humans could not imagine. Resultantly, AI now needed guard rails.

Developing an agentic AI system to achieve a goal (like generating compelling and continuously evolving multilingual content and ensuring it sells many SKUs) is now possible. Ensuring responsible AI usage and retaining control while availing the full benefits of AI is where the challenge lies. Agentic AI allows us to control two variables. These variables are the guard rails. When we (in an extremely specific manner) define the goal of the AI system and tightly restrict the data the system can access and use, we can leverage the computer power of AI models with minimal AI risk. That’s’ the essence of agentic AI.

Agentic AI is particularly useful in localization because it can:

• Process vast amounts of data
• Recognize patterns
• Make decisions quickly, accurately, and autonomously
• Adjust strategies to achieve its goal in an evolving environment
• Bring the human into the loop according to specifically defined event triggers

The nuances of language, culture, content, and readership are essential in localization and translation. By analyzing data from specific restricted sources, Agentic AI offers highly personalized localization strategies, adjusting content in real time based on product development trends, marketplace narratives, and user behavior. Agentic AI supercharges the concept of “continuous localization,” allowing for continuous content generation, translation, and auto-adjustment. (Though, of course, we should never forget measures to safeguard responsible AI.)

How Does Agentic AI Work in Localization?

An agentic system allows a company to trigger a flow of multilingual content with minimal data about the products or services. The AI system then uses carefully curated linguistic and cultural databases to create initial drafts of multilingual content. TM estates and glossary term banks are vital to keeping the agent on brand. The effect goes beyond mere translation. By referencing buyer conversations and buyer data, the AI system can incorporate cultural nuances and local idioms, ensuring content is engaging and relevant to each target audience. Companies can add a human in the loop for extra editing and reviewing at any point in the process.

As content circulates, Agentic AI monitors its performance across different markets. To continually refine and adapt the content, it tracks: 

• User impressions
• Interactions
• Social media trends
• Sales data and feedback

For example, if a particular phrase isn’t resonating well in one market, the workflow can flag it for adjustment or even automatically adjust it. Thus, agentic AI can ensure the message remains impactful and culturally appropriate.

Once content is optimized, Agentic AI handles publishing and distribution via traditional channel automation. It ensures the right content reaches the right audience at the right time. The system can automatically manage various distribution channels, from social media to websites, tailoring content format and style for each platform.

Quality assurance remains crucial in localization. Agentic AI includes robust self-correcting mechanisms and guardrails to ensure content maintains high standards while achieving business goals. It can identify and rectify issues, such as inconsistencies, biases, and inaccuracies. Furthermore, agentic AI systems can be trained to know when to call a human into the loop.

Agentic AI creates a self-fulfilling symbiotic multilingual content environment, ensuring your content lifecycles are continuous and totally focused on achieving your goals. Agentic AI generates content and then makes sure it meets your goals and supports your business. You can focus your labor and initiatives elsewhere while your content goes global.

Get in touch

As a localization industry leader, Lionbridge is uniquely positioned to build Agentic AI solutions for global content. Our Aurora AI orchestration platform exemplifies our readiness to embrace end-to-end generative AI solutions. Aurora combines AI’s scalability with our deep global network of expert linguists and testers.

We combine our cutting-edge Agentic AI technology with 25-plus years of experience and a network of more than 500,000 freelancers and language professionals. You can rely on Lionbridge to be at the forefront of technological localization and content advancements. Let’s get in touch.