The appeal is obvious. You have a strong support team in English. AI translation is fast, cheap, and getting better every month. Tools like DeepL, Google Translate, and Teams auto-translation handle the heavy lifting. Why hire or contract with someone in French when the technology handles the job?
Because customer support is not a memo exchange or a meeting transcript.
Support conversations are relationships
Support conversations are relationships. They happen in moments of frustration, when a user has a problem and your software isn't behaving the way they expected. In those moments, how your team communicates matters as much as what it communicates. A translated response can be grammatically flawless and still feel cold, distant, or dismissive.
AI translation has genuine strengths. For internal communication—syncing between teams, translating technical documentation, turning meeting notes into shareable content—modern translation AI is genuinely useful. The errors are rare and rarely consequential. A mistranslation in a Slack message gets caught and laughed about. A mistranslation in a support conversation becomes a customer service incident.
Where the gap widens: context, tone, and culture
The gap widens with complexity. AI translates words and sentences well. It struggles with context, tone, and cultural assumptions. A French user asking « Pourquoi votre logiciel ne fonctionne pas comme prévu ? » isn't just asking why the software doesn't work. They're expressing frustration about a broken expectation. An AI-translated response that addresses only the literal question—a bulleted troubleshooting list—misses the relationship dimension entirely. A French-speaking human hears the frustration and responds with empathy while troubleshooting.
French users are particularly skeptical of machine translation. They notice when responses feel generic or slightly off. They notice when the vocabulary doesn't match their industry. They notice when the tone doesn't match the gravity of the situation. These micro-signals accumulate into a larger message: the company isn't really committed to supporting the French market seriously.
The training problem and the liability question
There's also the training problem. Translation works for support tickets, but what about onboarding? What about helping a team learn how to use your software effectively? Training requires patience, example-building, follow-up questions, and adaptation to the learner's pace and knowledge level. An AI-translated training session leaves French users confused and frustrated. They're trying to understand a new tool while simultaneously parsing awkward phrasing. The cognitive load is brutal.
Then there's the liability piece. In certain regulated industries—finance, healthcare, legal—mistranslations in support or training can have legal consequences. Is your company willing to bet its compliance on AI translation quality? Unlikely.
The pragmatic approach
The pragmatic approach: AI translation is your first line of filtering. Use it internally to route French queries to the right team, to scan content for relevance, to speed up certain processes. But for customer-facing support and training, invest in a native French speaker who understands your software and your users. The cost difference is minimal compared to the reputational risk of getting it wrong.
Your French customers will feel the difference. And they'll stay.