How AI Translation is Changing Global Email Marketing

"You can near-perfectly translate a sentence and still completely lose the tone, humour, or that sensitive cultural nuance that makes things work in the first place," says Des Brown, founder of Email Expert Africa. "Brand risk carries a far higher cost than efficiency."

Brown has watched global email programs struggle with this tension for years. AI translation tools have become remarkably capable. They're faster and cheaper than human translators. But something gets lost when marketers treat translation as a solved problem.

The gap between "translated" and "localized" is where campaigns fail. A technically correct email that feels off to local readers doesn't just underperform. It damages trust. And at scale, those small disconnects compound into real brand risk.

73% of marketing ops professionals are actively using or experimenting with AI tools. Translation is one of the most practical applications. But the teams getting results aren't replacing human judgment. They're augmenting it.

What AI translation does well

AI translation has improved dramatically. The clunky machine translation of a decade ago bears little resemblance to modern tools.

For straightforward, factual content, AI translation works. Product specifications, technical documentation, transactional emails with standardized copy. These translate well because they're not trying to persuade or build emotional connection. The content follows patterns that AI has seen billions of times.

The accuracy improvements are measurable. Google Translate achieves 94% accuracy for Spanish, 90% for Tagalog, and 82.5% for Korean. DeepL and other specialized tools often score even higher on European languages. For factual content, these accuracy rates are often sufficient.

The cost savings are substantial. Traditional translation agencies charge $0.10-0.20 per word. AI translation runs 10-50x cheaper. For a global marketing team sending campaigns in twelve languages, that's the difference between translating everything and translating selectively. The AI translation market grew 25% year-over-year to $2.34 billion in 2024, reflecting how quickly enterprises are adopting these tools.

Where AI translation falls short

Brown's observation cuts to the core issue: language accuracy and brand voice accuracy are different things.

"Brand voice is a subtle set of behaviours," he explains. "Automation only follows specific rules. Having that human touch around why things are written for a particular language in a specific way is where human eyes tend to make the biggest difference."

Consider what happens when AI translates marketing copy:

A campaign that works in English might fall flat in French not because the words are wrong, but because the approach doesn't resonate. The casual, friendly tone that works in American English can read as unprofessional in German business contexts. The wordplay that drives engagement in one market makes no sense in another.

"Readers can sense if something feels off even though it's technically correct," Brown notes. This intuition matters in marketing. Email recipients don't consciously evaluate translation quality. They just feel whether the message connects or doesn't.

The hybrid workflow global teams are using

The teams getting results combine AI and human translation strategically.

The modern AI-powered translation workflow looks like this:

Step one: AI generates the first draft. Run the source content through AI translation. This takes seconds instead of days and costs a fraction of human translation. The output is grammatically correct and semantically accurate.

Step two: Human reviewers check for brand voice. Native speakers with brand knowledge review the AI output. They're not translating from scratch. They're editing for tone, cultural fit, and brand consistency. This is faster than full translation and catches what AI misses.

Step three: Build a feedback loop. Document the changes reviewers make. Use this feedback to train your AI tools or create glossaries that improve future translations. Over time, the AI output gets closer to your brand voice.

Step four: Manage variations in one place. Global campaigns need version control. Track which markets have which versions, who approved what, and when updates need to sync. Without centralized management, translation becomes chaos.

The cost savings hold up even with human review. Hybrid workflows (AI draft plus human edit) typically deliver 50-80% cost savings versus human-only translation. The review step adds cost back, but not nearly as much as starting from scratch.

What to look for in AI translation tools

Not all AI translation is equivalent. Enterprise marketing teams need capabilities beyond basic translation.

Glossary and style guide integration. The AI should learn your terminology. Product names, brand terms, phrases you always translate a specific way. Tools that can ingest your style guides produce more consistent output.

Translation memory. When you translate a phrase once, the tool should remember it. This maintains consistency across campaigns and reduces review burden over time.

Context awareness. Marketing copy translates differently than legal copy. The tool should understand what it's translating and adjust accordingly.

Workflow integration. Translation that lives outside your campaign creation platform creates handoff friction. Look for tools that work within your existing workflow rather than requiring exports and imports.

Variation management. Global campaigns need multiple language versions tracked together. When the source changes, all translations should flag for review.

Platforms like Knak address these requirements by integrating translation directly into the email creation workflow. Teams can translate, review, and manage variations without leaving the platform. For teams with existing translation vendors, translation API integrations connect external services directly into the workflow.

Human review at scale

"Human review is still insanely crucial," Brown emphasizes. "Especially at scale when things are so easily watered down or missed."

The challenge is operationalizing review when you're translating hundreds of emails into dozens of languages. Pure human review doesn't scale. No review at all creates brand risk. The answer is tiered review based on content type and risk.

This tiered approach concentrates human attention where it matters most. Low-risk transactional content doesn't need the same scrutiny as a major brand campaign. But the brand campaign absolutely needs native speakers asking Brown's essential question: "Does this actually sound like us?"

The localization gap most teams miss

Brown makes an important distinction between translation and localization. Translation converts words from one language to another. Localization adapts the entire message for a specific market.

"Many marketers assume that 'translated' automatically means 'localized,'" he observes. "Unfortunately, there is too much cultural and language-based nuance that direct translation and copy-pasting tend to miss."

Localization includes:

• Cultural references that resonate locally (holidays, events, shared context)
• Visual elements that work across markets (colors, imagery, layout direction)
• Offers and pricing adapted to local markets
• Timing aligned with local business hours and customs
• Legal requirements specific to each jurisdiction

AI translation handles the language conversion. Localization requires human judgment about what will actually work in each market. The teams that treat translation as the finish line end up with technically correct emails that underperform.

The data supports investing in proper localization. 76% of online buyers prefer products in their local language. This preference extends to marketing emails. A translated email might be understood. A localized email feels like it was written for that specific audience. The performance gap between the two is measurable in engagement rates and conversions.

AI translation and brand consistency

The deeper concern Brown raises is brand risk. Translation errors aren't just embarrassing. They erode the trust that marketing is supposed to build.

"Brand risk carries a far higher cost than efficiency, especially in the communication space," he says.

This reframes the AI translation decision. AI can translate faster and cheaper. That's established. The real question is whether the efficiency gains are worth the brand risk when human oversight decreases.

For most global marketing teams, the answer is hybrid. Use AI to handle the volume. Use humans to protect the brand. Build workflows that make this sustainable at scale.

The tools exist. 63% of marketers are already using AI in email marketing. The teams seeing results are the ones who understand what AI does well and where it needs human backup.

AI translation enables global scale

Global email marketing was once reserved for enterprises with translation budgets and localization teams. AI translation changes that math.

The cost dropped. A campaign that once required thousands in translation fees now requires hundreds. The speed increased. What took weeks now takes hours. The barrier to global marketing is lower than it has ever been.

Teams that once limited themselves to two or three languages can now realistically support eight or ten. Markets that were previously too small to justify translation costs become viable. The economics of global marketing have fundamentally shifted.

But the fundamentals of effective marketing haven't changed. Success requires understanding your audience. That understanding is cultural, not just linguistic. AI handles the language conversion efficiently and affordably. Humans provide the cultural intelligence that makes the difference between translation and localization.

The teams winning at global email marketing aren't choosing between efficiency and brand voice. They're building workflows that deliver both. AI for the first draft. Humans for the judgment calls. Centralized platforms to manage the complexity.

That's how AI translation is actually changing global email marketing. Not by replacing human judgment, but by making human judgment scalable across every market you serve.

See how Knak's translation features work.