Is learning new languages still relevant in the AI era?

Voice translation on demand. Conversations with automatic subtitles. Instant message conversions. 

Today, the ability to connect across languages fits right in our hands. Whether it’s for travel, healthcare translation services, or clinical research coordination, AI-driven language tools are bridging communication gaps faster than ever. 

But as these technologies evolve and become more seamless, a quiet question arises: 

Is learning another language still necessary? 

The evolution of real-time language tech 

Over the past ten years, AI in translation has advanced at an incredible pace. Tools for real-time interpretation and handheld translator devices have made their way into industries such as tourism, education, and public health. Around the globe, more people are asking whether mastering another language remains a critical skill, or if it belongs to a past, less automated era. 

Europe’s multilingual resilience 

Despite having some of the most advanced real-time translation technologies, European countries continue to prioritize multilingual education. Countries like Switzerland, Belgium, and Finland actively promote proficiency in multiple languages from a young age, not just for practical communication but to preserve cultural diversity and enable deeper cross-border cooperation. This European model highlights that language learning is seen as a cultural investment, not something to be fully outsourced to AI.

More than communication 

Seeing language as just a communication method downplays everything else it brings. 

Studies show that learning new languages strengthens mental agility, memory, and adaptability. Multilingual people often interpret subtle signals, read cultural cues, and deal with ambiguity more easily, critical in fields from medical interpretation to international collaboration. 

In the healthcare space, where Novalins provides certified medical translation services and supports translation of medical records, language goes beyond words. It becomes a channel for building trust, ensuring safety, and delivering compassionate care. 

And beyond its practical use, language unlocks connection. It carries humor, emotion, and cultural richness, elements no translation app or computer-assisted software can fully recreate. It’s what transforms a message into a moment of understanding. 

Speed without depth? 

Yes, real-time translation apps are a major step forward. They make it possible to communicate where barriers once stood, especially during emergencies or when managing clinical data. 

But there’s a trade-off. 

Anyone who has used a translation app or a simultaneous interpretation tool has likely noticed the delays, the glitches, or the missing emotional cues. The words may arrive, but the feeling doesn’t always come through. 

The World Economic Forum’s perspective 

The World Economic Forum has voiced concern over how AI might impact linguistic diversity. Many generative language tools prioritize dominant languages, like English, potentially pushing aside thousands of minority tongues. This bias can affect everything from casual conversations to medical document translation in less commonly spoken languages. 

Their recommendation? Find balance. Rather than replacing traditional learning, AI should enhance education and translation services. As they emphasize: “Language is core to identity, connection, and understanding. Technology should amplify, not override, that.” 

A reflection, not a conclusion 

At Novalins, we see firsthand how AI and human expertise can work together. Our clients use automated translation and online tools, but they rely on us for translating medical records, clinical documentation, and delivering human-level accuracy. 

So maybe the real question isn’t whether language learning is essential. It’s about what kind of communication we want. 

What types of relationships do we want to foster? What meaning do we hope to convey? 
There may not be one answer, but one truth remains: even the best translation solutions can’t always capture the full richness of human language.