How language AI cuts costs, reduces risk and fuels global growth

Amidst economic uncertainties and recession fears, today’s CIOs face mounting pressures to contain costs. Nearly two-thirds (63%) of CIOs now rank cost management as a top priority, with over 40% postponing discretionary technology spending this year. Yet despite these efforts, many are overlooking one of the most costly and persistent threats to operational efficiency: language and communication barriers. These challenges will only grow in scale and impact as the world becomes more globalized and connected.

According to a recent DeepL survey, language friction is widespread among enterprises – and expensive. Nearly 70% of enterprise executives reported encountering language-related operational friction on a daily basis. Currently, as many as 40% of U.S. companies lose between $500,000 and $2 million each year because of language barrier-related issues, including miscommunications that derail collaboration, create gaps in customer service and support and lead to compliance failures. This friction can be severe enough to stall plans for global expansion.

“Many U.S. companies assume that English is enough for business communication, but that’s a risky mindset – the reality is that only 18% of the world speaks English, and even within the U.S., over 60 million people speak a language other than English at home,” says Jarek Kutylowski, CEO and founder of DeepL, a leading provider of Language AI tools used by over 200,000 business customers around the world. “Our latest research underscores the huge impact that underestimating language barriers can have on enterprises, with 61% of executives admitting that they have miscalculated the extent to which language barriers are constraining their organizations’ expansion goals and bottom line.”

Clear communication isn’t optional in a tech-forward, globalized world

Breaking down linguistic and cultural barriers has always been essential for companies entering new markets, but it’s even more important today. In a digital-first world, customers expect accurate, relevant, grammatically correct and culturally sensitive communications from their favorite companies and brands. They also prefer to consume content in their native languages, with 74% of consumers saying they are more likely to buy from brands that offer customer support in their preferred language. 

But the impact of Language AI extends far beyond customer service. Companies that don’t localize their content – including websites, documentation, contracts and more – risk losing market share and falling behind competitors who communicate more effectively. Maintaining brand consistency and tone across languages is nearly impossible without scalable, high-quality translation infrastructure.

Internally, the stakes are just as high. Cross-border teams need tools that enable real-time, multilingual collaboration, otherwise, organizations risk delays, misalignment and fragmented decision-making. In highly regulated industries like healthcare and legal services, the risks associated with translation errors are even greater.  Systems handling sensitive or technical content must deliver precise, reliable translations to avoid compliance failures, reputational damage and the potential for costly fines.

Language AI opens the door to international business success

Language AI, a category of artificial intelligence that enables machines to understand, generate and translate human language, is quickly becoming the go-to solution for enterprises confronting these challenges, with adoption rapidly increasing. These systems power capabilities like real-time translation, content generation and speech recognition, relying on technologies such as natural language processing, machine learning and neural networks to deliver accurate, context-aware results. According to DeepL research, more than half of enterprises already use Language AI tools, and 96% plan to adopt them in the coming years.

“Failing to embrace these technologies now means risking falling behind,” Kutylowski says. “Seamless multilingual communication has become a business imperative for any enterprise operating internationally or aiming to expand its global footprint.”

In particular, domain-specific language solutions are gaining favor among leaders and CIOs because they offer better accuracy and performance than general-purpose AI tools, along with ease of integration.  These tools are trained on domain-specific data and even, in some cases, refined by human language experts, enabling them to deliver the accuracy and nuance required in business-critical environments.

This level of precision is especially important in high-risk sectors like healthcare, finance and legal services, where even minor translation errors can result in regulatory breaches, customer harm or costly legal consequences. Unlike general-purpose AI models – which may support many languages but lack contextual depth – specialized solutions consistently outperform when stakes are high. It’s no surprise that CIOs and business leaders are nearly twice as likely to prefer specialized tools over general-purpose alternatives (52% vs. 27%).

Choosing the best Language AI solution

Not all Language AI tools are created equal. As CIOs evaluate potential platforms, they should prioritize:

• Translation quality: Look for providers using proprietary large language models specifically trained for translation or language use-cases. Accuracy improves significantly when these models are fine-tuned on domain-specific data and enhanced through human linguistic input. In high-stakes industries, even minor errors can have outsized consequences – so quality, not breadth, should be the benchmark.
• Security and compliance: Ensure the provider adheres to enterprise-grade security standards. Look for features such as end-to-end encryption, regular third-party penetration testing and clear data handling policies. Compliance certifications like SOC 2 Type II, ISO 27001 and adherence to GDPR or industry-specific regulations are key indicators of a mature, security-first approach.
• Ease of integration: The best solutions integrate seamlessly into existing systems – including customer support tools, documentation platforms, product UIs and internal knowledge bases.

For organizations aiming to scale globally without compromising on quality, solutions like DeepL offer a proven path forward, combining enterprise-grade accuracy, security and seamless integration. In 2024 blind tests, professional translators found that DeepL’s next-generation language models required significantly fewer edits than any other platform, with Google and ChatGPT needing 2-3x as many edits to achieve the same quality.

In a climate where every dollar must be justified, Language AI delivers measurable savings and strategic value. Global leaders like Softbank, Mazda and Harvard Business Publishing rely on DeepL to power high-quality multilingual communication, accelerating growth, improving collaboration and reducing risk. For these organizations, Language AI is more than a tool; it’s transforming business relationships, boosting productivity and unlocking new markets.

To learn more about DeepL’s Language AI platform and how it can support your business, visit

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