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DeepL uncovers hidden costs of language barriers in global collaboration

Seoul, South Korea – October 28, 2026 – DeepL, a global leader in Language AI, today shared new insights from in-depth focus group discussions with Korean professionals, shedding light on daily communication challenges and what teams truly need from real-time voice translation. The insights follow a recent DeepL survey of 500 Korean professionals announced in March 2026, which revealed a gap between the perceived need for AI voice translation and its actual use: 89.8% considered the technology necessary for work, while only 35.8% reported using it. To explore this adoption gap, the study  brought together 16 professionals who regularly use foreign languages at work, organized across four focus groups. Through a guided trial of DeepL Voice’s translated captions during a simulated multilingual meeting, participants explored practical workplace applications and key requirements for enterprise adoption.

Language barriers impact participation and multiply preparation in global meetings

Participants described holding back questions, missing opportunities to respond spontaneously and relying on colleagues to speak on their behalf during global meetings. In several instances, foreign-language confidence, rather than subject-matter expertise, influenced who represented a team in global discussions. These experiences suggest that language barriers can affect whose expertise is heard and considered.

The burden of language friction also extended far beyond speaking and listening, driving employees into time-consuming routines, including preparing scripts and drafting responses to anticipated  questions before meetings, relying  on captions or multiple AI tools during discussions, and reviewing session recordings, transcripts or emails afterwards to confirm understanding.

Tool requirements also varied by language proficiency. Professionals comfortable working in a foreign language used AI primarily to check meaning, verify specialized terminology, or navigate unfamiliar accents. Less fluent speakers relied on real-time translation just to keep pace with the discussions and contribute  

What businesses need from real-time translation

Participants identified several requirements for enterprise-grade, real-time translation:

  • Accurate handling of industry terminology and internal expressions and numbers, along with strict security and data-handling practices
  • Minimal translation delays, clean handling of overlapping speech, and visual layouts that minimize the need to divide attention between captions and the conversation 
  • Proven value within existing tech stacks and workflows, particularly for organizations already using built-in captions or other AI tools

Participants highlighted high-impact use-cases across operations, including communication between headquarters and overseas offices, factories and suppliers, as well as international sales, customer service, and structured settings such as town halls.

More ways to follow multilingual conversations

To solve the challenge of dividing attention between captions and conversation during calls, he new DeepL Voice desktop app lets users choose between reading translated captions and listening to translated speech, depending on their needs. The app integrates directly with Zoom, Microsoft Teams and Google Meet, automatically detecting calls and displaying live translated captions in an always-on overlay. 

DeepL’s September update also made voice-to-voice translation generally available in 30+ languages for online meetings, in-person conversations and via the DeepL API. Voice preservation across 14 supported languages carries more of a speaker’s tone, rhythm and intonation into translated speech. The focus group trial covered DeepL Voice’s translated captions and did not include the newly announced voice-to-voice features. 

AMOREPACIFIC puts Language AI into everyday collaboration

AMOREPACIFIC’s use of DeepL Voice illustrates how real-time translation powers collaboration between its headquarters in Korea and overseas teams. Since introducing the solution, monthly meeting volume using DeepL Voice has grown more than threefold, from approximately 20-30 sessions to more than 100 per month, with employees reporting lighter communication burdens and higher meeting engagement.

The company’s deployment also reflects the importance of consistent terminology and compatibility with existing workflows, both raised in the focus groups. DeepL Voice’s glossary functionality supports maintaining standardized translations for brand and business terms, while its integration with Microsoft Teams allows employees to use translated captions within their established meeting workflows.

“Language barriers don’t just make communication harder, they also impact who can speak up, who gets heard and how much extra work teams have to take on just to stay aligned. For businesses operating across markets, that can slow decisions, limit access to expertise and make it harder for teams to move quickly,” said Jarek Kutylowski, founder and CEO of DeepL.Real-time translation removes that friction. With DeepL Voice, we’re helping businesses collaborate more effectively across languages without changing the way their teams already work.”

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About DeepL

DeepL is a global AI company building the language infrastructure that powers global business. More than 200,000 business teams and millions of individuals use DeepL's Language AI platform to communicate globally, collaborate and operate across languages in real time. By combining breakthrough AI models with enterprise-grade security and privacy, DeepL enables organizations to work seamlessly across markets and cultures. Founded in 2017 by CEO Jarek Kutylowski, DeepL now has more than 900 employees and is backed by leading investors including Benchmark, IVP and Index Ventures. Learn more at www.deepl.com.