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AI is Critical for Languages you Can’t Offshore

I like to think of languages like a TCP/IP protocol for brains. They enable humans to transmit data from one place to another, via soundwaves. As much as they unite us, they can create an invisible barrier between us, something that often surfaces in customer service when dealing with customers across the globe, or even within a single country.

With labor shortages to contend with, and even more so when it comes to multilingual agents or finding a lower cost location that speaks the language you need, they can present a very concrete barrier to serving your customers, and especially so for smaller languages.

For languages you cannot offshore, Artificial Intelligence is not just critical, but likely the only solution you’ll have. Here’s why and how to use it to overcome your CX challenges.

Offshoring & A Quick History Tour

Offshoring customer service has been a tried-and-true method for reducing costs while attempting to maintain service levels. Initially, it seemed like a win-win, lower costs for companies and economic growth for offshore locations. Yet, when it comes to customer service, especially in languages spoken by a smaller population, offshoring hits a snag. The talent pool in offshore locations for these languages is often limited or non-existent.

The reality is, countries with a long colonial history that have spread their language across the globe, such as the UK, US, Netherlands and France, have many options. Yet, if you’ve got a more wholesome history, you may find nearly no one outside your borders knows your language. The worst-case fallback is usually offering English as an addition or backup during off-hours, as many customers can at least speak it as a second language.

But let’s be honest, that’s still few people’s first choice. And surprisingly, even larger languages like German and Italian can suffer from the same issue as they are spoken almost entirely in a single country. So, what is a customer-centric company to do when their customers speak languages like Danish, Georgian or Estonian? AI can assist by handling that real-time translation -- no matter the language so agents and customers can communicate without barriers. 


Acronym Salad: AI, NLU, LLMs and ML

Luckily for you, we’ve never lived in a point of time with better technology related to languages or access to them. Let’s quickly dissect the acronyms above so we can use them:

AI – Artificial Intelligence

CAI – Conversational AI

NLU – Natural Language Understanding

LLM – Large Language Model

MT – Machine Translation

STT – Speech to text

TTS – Text to speech

These technologies combined form the backbone of AI's capability to understand and interact in human languages, including smaller ones.

Conversational AI, whose core is NLU enables AI to comprehend user queries in a natural, conversational manner, identify user intents and direct them to the appropriate service process (whether self-service or handover). Conversational AI also integrates and orchestrates your enterprise backend systems to make the processes possible and automated.

LLMs, powered by advancements in Generative AI, allow for dynamic generation of human-like text, enhancing the AI's ability to converse with responses created on-demand based on conversation context versus standardized replies. Finally, ML ensures that the AI learns from each interaction, constantly improving its understanding and responses.

Leveraging AI for Languages You Can’t Offshore

For languages that you can't find offshore solutions for, AI is your only solution to augment your workforce and serve off-hours. AI Agents, empowered by the technologies mentioned above, can provide customer service in virtually any language, including those spoken by smaller populations.

These AI Agents are not constrained by geographical locations or the availability of human agents proficient in specific languages. They can be quickly trained in the nuances of any language and can provide consistent, 24/7 support to customers.

One major telecommunications provider, serving a market of about 5 million people in the only country that speaks their language, recently ran up against this challenge. There are rarely dedicated NLU models for such languages, but they were able to take a universal language model, perform some additional training and quickly meet the labor gap plaguing their contact centers as well as offer service 24/7.

Yet, the benefits don’t stop at pure self-service. Another option is real-time translation for voice or chat. Translating a digital text-based interaction is straightforward today, yet what happens when a customer calls, speaking say Estonian and your agent only speaks English? Best of all, this isn’t on a roadmap somewhere. It exists today and can already be deployed. The focus of this article is technology, but I’d be remiss if I didn’t mention the potential cost savings involved here.

A single AI Agent can serve hundreds of thousands to millions of customers a year in everything from Norwegian to Klingon if you want. When considering North American and European labor costs to serve customers in their own language, imagine cutting half your demand purely via AI Agents and self-service and say the other by offshoring to the Philippines for example, where English speakers could still help Danes, Czechs, Turks, Vietnamese and others using real-time voice and text translation.

Serving international markets is an evergreen challenge for companies across the globe. Yet, AI and language technologies are so advanced today, that the language barrier is a thing of the past, particularly for those struggling to meet the needs of those who don’t speak a major world language. The future is today, for those willing to take the step forward.