Leveraging AI Beyond Translation

Because Buyers Want Much More Than Translations

While preparing the theme for this week's LocLunch Dallas my good friend Erica Haims reminded me how Localization buyers are typically interested in much more than just language when they engage a Language Services Provider. Traditionally, though, LSPs have not always done a stellar job of going much beyond language services. Now that AI offers an opportunity for a much more holistic approach shouldn't we be taking advantage?

Imagine you are a mining tool manufacturer looking to enter the Chinese market successfully. Translating your materials in Simplified Chinese is but one tiny aspect of your ultimate objective to conquer the market. ?You have a powerful tool designed for efficiency and precision, and you want to make sure it reaches the right customers. What if your LSP could help out with an AI-driven globalization integration? Utilizing their LLM application you can now revolutionize the way you engage with potential Chinese buyers and streamline the sales process.

Picture this scenario: a Chinese customer interested in purchasing your mining tool accesses your company's mobile application. With the application connected to LLMs and various data sources, such as your product catalog, inventory, customer information, order history, and other relevant data, it can provide much more than a simple product list.

Suppose the customer provides specific details about their mining requirements and project specifications. In that case, the application powered by LLMs can offer visualization tools and design aids, enabling the customer to envision the perfect solution tailored to their needs. Moreover, with access to the customer's postal code, the application can instantly inform them about nearby stores with your mining tool in stock, ensuring a seamless and efficient purchasing experience.

But the LLM-based integration doesn't stop there. Drawing insights from the customer's purchase history, it can intelligently suggest additional services or support they might need for their mining project. For instance, if the project appears to be complex or requires specialized assistance, the application can recommend professional contractors or experts near the customer's location, along with their contact information.

By integrating LLMs into your localization strategy, you can elevate your mining tool sales in China to new heights of efficiency, personalization, and customer satisfaction. The power of LLM-driven applications opens up a world of possibilities for seamless customer interactions and optimized buying experiences, positioning your mining tool as a top choice in the Chinese market.

Should we become GSPs instead of LSPs?

The emergence of Artificial Intelligence (AI) marks a transformative paradigm shift comparable to the advent of the internet in 1994. Corporations worldwide are now racing to integrate AI into their business operations. Should language services providers reposition themselves as globalization providers?

Before the release of ChatGPT in the fall of last year, AI was pretty much something only the MAMAA (Meta…formerly Facebook, Amazon, Apple, Microsoft and Alphabet…formerly Google)) companies were dealing with. Today, language industry businesses of almost any size find themselves grappling with the question of how to integrate the power of AI.

While in the localization industry, the most obvious application for AI is in the continued advance of automated translation models there could be additional ways to leverage these new technologies to gain competitive advantages. One of the most groundbreaking developments in this domain is the utilization of Generative AI and Large Language Models (LLMs). LLMs are far more than just tools for writing blog posts or coding assistance; they are rapidly becoming an indispensable part of the application stack.

Over the past couple of months, I have become fascinated with how we are going to build AI-first businesses in localization. How do we adjust to the new reality of truly using this new Artificial Intelligence technology to power our operations? How do we truly leverage these new technologies beyond their obvious use in automated translation processes?

Since I launched the AI-in-Loc newsletter I find myself more and more in a consultative AI role. I am being asked where I think AI will play the most important role in the language industry going forward.

Pre-ChatGPT, these weren’t really questions on people's radar, much less ones that had good answers.?Today we have just started peeling back the layers of the onion. Beyond the surface, there are a lot of sub-questions that that localization firms need to consider:

• What should people learn
• Who should businesses hire
• Where should businesses start
• Why do certain things
• Why not do other things
• What ethical guardrails should exist + more

Harnessing AI is becoming easier

The application of LLMs is not a distant science fiction dream anymore. Numerous localization organizations are actively working on projects that incorporate generative AI not just in automated translation applications.

Contrary to the misconception that LLM-based projects are exclusive to large enterprises, they are, in fact, accessible to a wider range of developers. You don't need an extensive background in machine learning or data science to build LLM-based applications. With just the ability to make a database call and an API call, developers can bring to life applications with unprecedented levels of personalized context, a feat that was once unimaginable but is now achievable with the right database and an LLM like GPT-4.

Improving CX Is Low-Hanging Fruit

If pivoting to full-on holistic Globalization seems too ambitious we should at least focus on helping our customers improve their Customer Experience, wouldn't you agree? The integration of Generative AI and Large Language Models into the localization process presents us with a real opportunity to revolutionize the way we provide services and interact with our users. By tapping into the power of LLMs and leveraging extensive databases, there is a new opportunity to provide customers with expertly curated, personalized, and prescient information. As accessibility to LLM technology continues to grow, we can expect to see a proliferation of innovative and engaging applications that redefine customer support in the digital age.

Many predict that the future of mobile applications lies in creating generative AI interfaces, or "agents," that leverage vast amounts of data knowledge. This approach, already gaining momentum, enhances dynamic interaction, facilitates access to extensive public and proprietary data, and enables adaptation to specific user situations. Applications built on LLMs offer unparalleled power and engagement, revolutionizing the mobile app landscape.

The technology behind LLMs has evolved rapidly, making it increasingly accessible to developers. Virtually anyone with the right database and appropriate APIs can now create these enriching user experiences.

Contrary to the common perception of AI agents as simple chatbots, LLM-powered applications go beyond offering canned responses from an FAQ. These advanced applications tap into the right data sources, enabling them to provide expertly curated, specific, and rich information. The result promises to be an uncannily prescient interaction that significantly enhances the user experience.

With their ability to enhance speed, scale, and consistency, LLMs are poised to automate tasks that were once exclusively handled by human specialists.

The most profound impact of LLMs is observed in domains reliant on agent-led service and support. In the past, organizations heavily relied on human agents who possessed extensive knowledge of corporate policies and procedures documented in large bodies of text. These agents had to follow strict rules while also interpreting and handling edge cases not explicitly covered in the documentation.

Training agents to be proficient in their roles was a time-consuming process. Moreover, the challenge was exacerbated by high turnover rates, making it difficult to maintain a consistently skilled workforce to staff call centers and support desks.

In response to these challenges, businesses have been exploring ways to offload customer requests to online platforms, but such attempts often fell short due to the limitations of the available technologies. However, with the emergence of advanced LLMs, the tide is turning, and a new era of customer support and service is dawning.

AI promises to enable applications to deliver expertly curated information tailored to individual user needs. By accessing extensive databases, these applications can respond with a depth of knowledge and understanding that was previously unattainable. Users can now receive detailed and accurate responses to their queries, fostering a sense of trust and satisfaction.

Through continuous interactions and access to vast data, LLM-based applications can personalize their responses to users' preferences and behaviors. This level of personalization can create a more immersive and enjoyable experience, hopefully fostering long-term engagement and loyalty.