AI for Translation and Localisation of Marketing Content

A marketing message that works in one country can fall flat, confuse people or even offend them in another. Translation turns words from one language into another. Localisation goes further and adapts tone, examples, formats, humour and offers so the message feels native to the reader. AI has made the first draft of both far cheaper and faster, which is why more small teams are now publishing in several languages.

This guide explains how to use AI for translation and localisation of marketing content without embarrassing mistakes. You will learn how to prepare source copy, brief the tool, handle brand terms, review output when you do not speak the language, test with real readers, and build a simple workflow. The advice is general and applies to any language pair and any AI tool.

Translation versus localisation

Many teams treat these as the same task. They are not, and the difference decides how much effort you need.

Translation converts meaning. Localisation adapts everything around the meaning so the content feels written for that market. A translated slogan may be accurate and still sound strange. A localised one is rewritten, if needed, to land well.

Element	Translation only	Localisation
Words	Converted closely	Adjusted for natural local phrasing
Examples	Left as they were	Swapped for locally familiar ones
Dates and numbers	Often unchanged	Formatted to local conventions
Tone	Carried over literally	Matched to local expectations of formality
Calls to action	Translated word for word	Reworked for what local readers actually do
Images and colours	Unchanged	Checked for local meaning

A quick way to decide

Ask three questions. Would a local reader notice that this was written elsewhere? Does the message rely on a shared cultural reference? Is the goal to persuade rather than simply inform? If the answer to any of these is yes, plan for localisation rather than plain translation, and budget extra review time.

For a basic help page, translation may be enough. For a homepage, ad or launch email, you usually want localisation.

Where AI helps and where it does not

Modern language models handle many common language pairs well. They can keep a consistent voice, follow a glossary and adapt to a requested tone. They are weaker with less common languages, specialist vocabulary, regional dialects and subtle cultural cues. If you want to understand why a model can sound fluent and still be wrong, read what a large language model is.

Good uses

• First drafts of product pages, emails and social posts.
• Keeping terminology consistent across many files.
• Producing several tone options for you to compare.
• Back-translating text so you can sanity check the meaning.
• Explaining why a phrase is formal, casual or ambiguous.

Risky uses

• Legal terms, safety information and regulated claims.
• Anything where a mistranslation causes harm or cost.
• Humour, wordplay and emotional storytelling.
• Languages where you have no reviewer at all.

The more public and consequential the content, the more human review it needs.

Why quality varies by language

A model has usually seen far more text in widely used languages than in smaller ones, so quality tends to be uneven. You may find that one language pair reads smoothly while another produces stiff or odd phrasing. Do not assume that a good result in one market means a good result everywhere. Run a small test for each language, and rely on a native reviewer more heavily for the languages where you cannot judge the output yourself.

Preparing your source copy

Quality in, quality out. Source copy that is clear in your own language is much easier to translate or localise, by a person or a model.

Simplify before you send

• Use short sentences with one idea each.
• Remove idioms such as hit the ground running or low-hanging fruit.
• Avoid puns, rhymes and slogans that rely on sound.
• Spell out abbreviations on first use.
• Keep one term for one thing. If you say customer in one place and client in another, the translation may split them.
• Flag text that must not change, such as brand names.

Keep a clean source file

Store the final approved source text in one place and treat it as the single version of the truth. If copy changes after translation has started, note exactly what changed so that only those lines are redone. Translating from several slightly different versions is a reliable way to create inconsistent pages across markets.

Add context

Short strings without context are the biggest cause of bad translation. A single word like Book could be a verb or a noun. Note where each string appears, such as a button, a headline or an email subject, and who reads it.

Briefing the AI for a localised draft

A good brief carries more weight than a clever tool. The advice in how to write better prompts applies here. Include the following:

1. Source and target. Name the language and the regional variety, such as Spanish for Mexico or French for Canada.
2. Audience. Describe who will read it and how formal to be.
3. Purpose. Say whether the text sells, informs or reassures.
4. Glossary. List terms that must stay the same or be translated a set way.
5. Constraints. Give limits such as character counts for buttons or subject lines.
6. Output. Ask for the final text plus a short list of choices it made and anything it was unsure about.

A sample brief structure

You can reuse a simple structure: the market and variety, the reader, the goal of the text, the tone, the glossary, the length limits and the output format. Keep it in a shared document so that everyone on the team briefs the tool in the same way, and so improvements to the brief benefit every future project.

That last point is valuable. When the tool tells you where it hesitated, your reviewer knows where to look first.

Glossaries and style notes that keep you consistent

A glossary and a style note are the cheapest quality tools in localisation. Create one per market and reuse it in every brief.

Item	What to record	Example of the kind of note
Brand names	Never translate	Keep the company and product names unchanged
Key terms	Approved translation	One agreed word for each product feature
Forbidden words	Terms to avoid	Words with unwanted local meanings
Tone	Formal or friendly	Use formal address with new customers
Formats	Dates, currency, units	Local date order and measurement units
Punctuation	Local conventions	Quotation marks and spacing rules

Start small. Ten to thirty terms covering your brand, your product features and your most common calls to action is enough for a first version. Add new entries whenever a reviewer corrects something, so the glossary improves with use.

Ask a native speaker to approve each glossary once. After that, the AI can apply it quickly, and your reviewers spend time on judgement rather than on fixing the same inconsistency repeatedly.

Cultural adaptation beyond the words

Localisation covers more than language. Look at every element a reader will notice.

Readers notice small signals of care, such as a correctly written local address, a familiar payment option or a date in the order they expect. These details tell them that the business understands their market, and they often matter more than clever copy.

Things to check

• Examples and references: sports, holidays and public figures rarely travel.
• Colours and symbols: meanings vary between cultures.
• Humour: usually needs rewriting, not translating.
• Social proof: use customer examples that make sense locally, and only real ones.
• Offers and payment: local payment habits and delivery expectations may differ.
• Formality: some languages have formal and informal address, and the wrong choice feels odd.
• Text direction: some languages read right to left, which affects layout.

An example of adaptation

Imagine a campaign built around a sports metaphor that is popular in one country and unknown in another. A literal translation would leave readers puzzled. Localisation replaces the metaphor with an everyday image that readers in the new market already understand, while keeping the same core promise. The idea survives, and the wrapper changes.

AI can suggest cultural issues to check, but treat its suggestions as prompts for a local reviewer rather than a verdict. A model can repeat stereotypes, so ask people from the market for their view.

Reviewing output when you do not speak the language

Most small teams do not have a fluent speaker in every market, and that is normal. The goal is not perfection on day one but a process that catches the biggest errors before readers see them.

Most small teams can still build a reasonable review process. You can still build a reasonable review process.

1. Back-translate. Ask a second, separate AI session to translate the result back into your language and compare it with the original. Differences point to problems.
2. Ask for alternatives. If three versions of a line are very different, the meaning may be ambiguous.
3. Check the numbers. Confirm prices, dates, percentages and names carried over correctly.
4. Use a native reviewer. Pay a freelancer or ask a trusted contact to review public pages, even briefly.
5. Start small. Launch one page or one campaign first, then learn before you expand.

What to give your reviewer

Make the reviewer’s job easy. Send the source text, the draft, the glossary, the style note and the list of uncertain choices the AI produced. Ask specific questions, such as whether the tone is too formal, whether any phrase sounds unnatural and whether anything could be misunderstood. Specific questions get better feedback than a general request to proofread.

Back-translation is a useful sanity check but not proof. A text can back-translate neatly and still sound unnatural. Only a fluent reader can judge naturalness.

Content types and how much review each needs

Different content carries different risk. Use this guide to decide where to spend your review budget.

Content type	AI first draft	Human review	Why
Social posts	Yes	Light native check	Tone and slang can misfire
Email campaigns	Yes	Native review	Subject lines are fragile
Landing pages	Yes	Full native review	Directly affects conversion
Ads	Yes	Full review and policy check	Short copy, high visibility
Product help pages	Yes	Spot check	Clear and literal text
Legal and policy text	Reference only	Qualified professional	Errors carry real consequences

For anything involving contracts, regulated claims or privacy notices, use a qualified professional. This is general information, not legal advice.

Searching and finding content in other markets

People search differently in different languages. A direct translation of your English keyword may not match what locals type. Treat search as a localisation task in its own right.

Practical steps

• Research keywords in the target language rather than translating your list.
• Use the local phrasing in titles, headings and meta descriptions.
• Set up the correct language and region tags on your pages.
• Link localised pages to each other so search engines understand the relationship.
• Check that your answer-style content is clear for AI search tools in that language too.

Our guide to AI keyword research explains how to use AI suggestions as a starting point and then check them. The same caution applies even more when the language is not your own, and the broader ideas in the AEO guide carry across languages.

A repeatable localisation workflow

Turn the steps above into a routine your team can follow every time. Name an owner for each market, so that questions from reviewers and readers always reach the same person, and agree how long each stage should take so launches do not stall waiting for feedback.

1. Finalise and simplify the source copy.
2. Write or update the glossary and style note for the market.
3. Brief the AI with audience, purpose, glossary and constraints.
4. Generate the draft and the list of uncertain choices.
5. Run a back-translation check on key sections.
6. Send to a native reviewer with the uncertainty list.
7. Apply fixes and update the glossary with new decisions.
8. Publish, measure and gather feedback from local readers.

If you later want to automate parts of this, see how to build your first AI workflow without code. Keep a human approval step before anything goes live.

Pre-publish localisation checklist

Use this list before you publish any localised piece, and keep a copy with the project files so you can show what was checked and by whom.

• Brand and product names unchanged.
• Numbers, prices, dates and units correct for the market.
• Regional variety of the language is right.
• Tone and formality match local expectations.
• No idioms or references that only work in the source culture.
• Buttons and headlines fit the layout.
• Native reviewer approved the final text.
• Links, forms and contact details work for local users.
• Claims comply with local advertising rules, checked by a qualified person where needed.

Frequently asked questions

Is AI translation good enough to publish without review?

For low-risk internal or reference text it can be. For public marketing, especially landing pages and ads, have a fluent human review it. Small errors damage trust quickly.

Do I need a translator if I use AI?

You still need a fluent reviewer for important content. The AI reduces the cost and time, because the reviewer edits a good draft instead of writing from scratch.

How do I keep my brand voice in another language?

Write a short voice description with examples of good and bad phrasing, add it to your glossary and include it in every brief. Have a native speaker confirm that the tone sounds right.

Should I translate my whole website?

Not necessarily. Start with the pages that matter most to that market, such as the homepage, main product pages and contact details, then expand as you learn what readers use.

Can AI localise images and video?

It can help with captions, scripts and subtitles. Visual choices still need a human who understands the culture. Check any generated imagery for accuracy and appropriateness.

What data should I keep out of translation tools?

Avoid sending confidential contracts, personal data or unreleased plans to tools you have not approved. See our guide on protecting company data.

Conclusion

AI has lowered the cost of reaching new audiences, but good localisation still depends on judgement. Prepare clear source copy, brief the tool carefully, keep a glossary per market and put a fluent reader between the draft and the public. Start with a small test, learn from local readers and expand only when the results justify it.

To sharpen the briefing step, revisit how to write better prompts, and before you publish anything, run through how to check AI output for mistakes. A careful process will serve you better than any single tool.