The Future of Localisation: AI, Sitecore, and the Path to Scalable Multilingual Personalisation

The Future of Localisation: AI, Sitecore, and the Path to Scalable Multilingual Personalisation

Global Ambition, Local Reality

Major brands have long grappled with a familiar challenge: how to speak to the world without sounding generic or worse, irrelevant. Whether it’s a global bank rolling out financial education tools or a retail giant launching campaigns across 20 regions, the ability to localise content with both speed and nuance is business-critical.

Traditionally, localisation has meant human-led translation. While this ensures linguistic accuracy and cultural sensitivity, it also leads to delays, inflated costs, and manual workflows that stifle agility. In the age of real-time personalisation and content velocity, is this still sustainable?

95% of all brands who use Translation historically rely on Google Translate and Human translators. AI has emerged as a game-changer. Tools like DeepL, Azure Translator, and ChatGPT-driven workflows promise instant, scalable translation. But the rise of AI introduces a new question: Has technology evolved enough to replace human translators completely? And how do platforms like Sitecore help brands operationalise localisation and personalisation at scale, without losing their brand voice?

Let’s unpack these questions and show you what tangible steps Marketing Leaders can take to deliver better, faster, and more localised experiences that drive conversion and loyalty.


Article content
Getting the messaging right is very important (image - DaLL-E)

 Is AI Translation Enough?

The answer is: not yet…... but we are getting close.

AI translation has drastically improved, leveraging neural networks and contextual language models to produce fluent, coherent translations. According to a 2023 CSA Research study, over 70% of enterprise marketers use AI translation in some form, often as a first pass to accelerate delivery.

But there are caveats:

  • AI still struggles with tone, idiomatic expressions, humour, and culturally sensitive content.
  • Compliance-heavy sectors like financial services, healthcare, or government, require human oversight for regulatory accuracy.
  • Brand voice consistency remains a major weakness in out-of-the-box AI tools.

Take Amazon’s 2020 Swedish launch. Relying heavily on machine translation, the platform mislabelled products in ways that were not just inaccurate but offensive. The backlash was immediate and entirely avoidable with basic human QA.

Marketing takeaway: AI can accelerate localisation workflows and reduce costs but without human quality assurance, you risk brand damage at scale.

Article content
Show the balance of AI speed vs human oversight. (image - DALL-E)

The best approach today is a hybrid model:

  • Use AI for speed and scale
  • Apply human review for tone, accuracy, and nuance
  • Integrate translation governance into the content workflow

This model supports both agility and accountability especially when content needs to be live in 30+ languages within days, not weeks.

Sitecore: Built for Multilingual Complexity

Sitecore has long been a leader in enterprise-grade multilingual content management.

Sitecore XM Cloud (and XP before it) supports:

  • Structured language versions for each content item
  • Language fallback hierarchies
  • Editorial workflows per language and region
  • Role-based access for in-market teams
  • Translation connectors and APIs to integrate with TMS platforms (e.g. Smartling, Lionbridge, Memsource)

Why this matters to you? This means brands can operate global centralised campaigns with localised content variants from a single platform without duplicating content or fragmenting brand governance.

More importantly, Sitecore’s multi-language publishing model enables both “core” and “market-led” localisation strategies. For instance:

  • HQ controls base content and brand tone
  • Regional teams adapt messaging and calls-to-action (CTA) to local context

This flexible model works whether you are a bank operating in ASEAN markets or a fashion retailer scaling across the EU. You could be a Mining or Construction giant that needs different language and content in multiple geographies.

What About Personalisation?

Localisation and personalisation are often treated as separate workflows—but they shouldn't be. Real relevance comes when you combine both.

Sitecore Personalize allows real-time, session-based targeting by:

  • Country, language, browser locale
  • Device, referrer, campaign ID
  • Behavioural signals (pages viewed, goal completions)
  • Embedded decisioning logic for dynamic content delivery

Marketer Insight: Combining localisation with behavioural data drives lift in conversion, engagement, and relevance, even in anonymous sessions.

So, a visitor in France could see content in French with CTAs geared toward mobile conversion, while someone in Canada gets a different layout in English with tax-incentive messaging and someone in Montreal, Canada could see it in French Canadian. This can be done without persistent user identity, ideal for top-of-funnel engagement.

Article content
Depict structured localisation in action. (image - DALL-E)

But what if you want memory across sessions? That’s where Sitecore CDP enters the mix.

Sitecore CDP: From Goldfish Memory to Persistent Insight

Sitecore XM Cloud and Personalize offer powerful real-time targeting…. but they forget. Visitor data isn’t stored across sessions unless tied to a persistent ID. The experience resets after each visit or session for Sitecore XM Cloud or Sitecore Personalize on its own.

Sitecore CDP solves this issue with:

  • Persistent user profiles across sessions and channels
  • Real-time ingestion from CRM, loyalty, app, POS, and web
  • Lifecycle segmentation and journey orchestration
  • Identity stitching and consent-aware targeting

Let’s take a real-world example.

A logged-in banking customer from Malaysia visits your “Travel Credit Card” page. Next week, they’re browsing Instagram and see a relevant offer personalised to their location, income segment, and lifecycle stage, still in Bahasa Melayu.

That orchestration doesn’t happen with session-only tools. It requires a CDP that can store, segment, and activate customer data across touchpoints.

Why this matters: Persistent data turns reactive websites into proactive experiences, ones that know your customer, not just their last click.

Sitecore Stream: The Emerging AI Power Layer

What about content creation and translation itself?

That’s where Sitecore Stream is gaining traction. Still evolving, Stream introduces generative AI into the Sitecore stack as a “co-pilot” for marketers and authors. It’s not just a gimmick, it unlocks practical advantages for multilingual content delivery:

  • AI-assisted content creation with tone and brand-guardrails
  • Dynamic generation of language variants
  • Contextual suggestions for CTAs or localisation tweaks
  • Content testing variants for different segments

Imagine entering a product brief in English, and Stream returns draft versions in Spanish, German, and Simplified Mandarin, aligned with tone and audience. Editors simply review, refine, and publish.

For brands with hundreds of product pages or campaign variants, this radically reduces time-to-market.

Marketer Insight: Stream reduces manual lift in content production, accelerating go-to-market timelines while still staying on-brand.

Real-World Applications

1. Retail: Local Promotions at Scale

A global fashion retailer launches seasonal sales in 15 countries. Historically, the local marketing teams handled content editing in spreadsheets, passed to translation agencies, and fed back into CMS. This took weeks.

Now, they could use:

  • Sitecore XM Cloud for content structuring
  • Azure Translator via webhook for draft translation or via building an API integration to a translator or we could explore using Sitecore Connect.
  • Sitecore Personalize to tailor offers by market
  • Stream to generate promotional blurbs with local idioms

Time-to-live would shrink from 120 days to less than 15 days.


Article content
Tangible but gettable results! (image - DALL-E)

2. Finance: Hyper-Personalisation in Regulated Markets

Lets take another hypothetical example and this time a major brand in the Financial Services space in Europe that uses Sitecore CDP to unify data from website, call centre, and mobile app. It creates:

  • Language-aware nurture flows (English, French, Dutch)
  • Predictive segments (first-time buyer vs. churn risk)
  • Web and email personalisation through Sitecore Personalize and Marketo that honours GDPR and user preference

By combining CDP and Personalize with localisation, they could boost engagement by at least 15% and reduced unsubscribe rates by a number they would be very happy with!

Can We Do Hyper-Personalisation in Multiple Languages?

Yes, with the right architecture.

It requires:

  • Structured content and taxonomy
  • AI-assisted translation pipelines – MCP and Sitecore Imagine using GenAI prompts to trigger AI translation of content direct into Sitecore content for different pages on the website.
  • Identity resolution and data stitching
  • Multi-language segmentation
  • Consent-aware orchestration tools

The result? A visitor in Tokyo and a shopper in Madrid can each receive messages tuned to their language, behaviour, lifecycle stage, and channel preference.

Marketer Insight: But success depends on governance, training, and tooling. Hyper-personalisation across languages isn’t just a tech challenge, it’s an operational one. And it’s one that delivers!

Cade Whitbourn , 3 time Sitecore Strategy MVP had this to say, “MCP is potentially a game changer in AI translation. Sitecore’s Model Context Protocol (MCP) combined with LLM agents can automate and dramatically simplify content translation workflows within Sitecore — reducing effort to just a few natural language prompts, with minimal manual configuration or coding.

Beyond translation, its an approach that can unlock real agentic AI doing all sorts of things directly in Sitecore via prompts, abstracting out the role of content authors, developers, marketers and many more.”

Why Human Oversight Still Matters in AI-Driven Content

AI is accelerating how we localise and personalise digital experiences, but let’s not confuse speed with precision. While generative AI can help scale content creation and translation, the human touch is still essential for quality, trust, and brand alignment.

Real but basic Examples: 3 Videos, 3 Levels of Intervention         

To illustrate this, I ran an experiment. I had three videos created using AI tools — and each showed why human intervention makes or breaks the result.

  1. Video 1 Watch Here I let the AI run almost unchecked. Gave it a prompt on what I planned on achieving and asked it to create the video for me. The voice over was not part of the Video. The result? The video while looks nice and was functional, it lacked nuance, missed some context, and felt generic. It didn’t land the message as clearly or confidently as it should have.
  2. Video 2 Watch Here This version was better. I gave the AI clearer prompts, guided the output, and made some manual edits. The messaging improved, but it still had factual or tone inconsistencies that slipped through. The text on the video was still Gibberish to a certain extent.
  3. Video 3 Watch Here By this stage, I layered in multiple AI tools, cross-checked facts using different LLMs, applied stricter prompt engineering, and polished the visuals using Canva. The difference was stark: It was sharper, more accurate, and on-brand.

The lesson? At least today in 2025, AI needs human guidance, not just for fact-checking, but for tone, visual relevance, compliance, and audience fit. Without human intervention, you risk amplifying inaccuracies at scale.

A Phased Maturity Model

Article content
The Strategic path is clear. Learn to Walk before running.

Brands don’t leap to multilingual hyper-personalisation overnight. A smart progression looks like this:

Crawl

  • Use XM Cloud + AI Translation (with human QA)
  • Localise content by market manually
  • Personalise by session-based context

Walk

  • Add CDP to unify data across sessions and platforms
  • Use basic segments (e.g. geo, persona, funnel stage)
  • Introduce translated content variants into journeys

Run

  • Automate multilingual content creation with AI (Stream)
  • Deliver dynamic, predictive experiences by region and persona
  • Personalise across web, email, app, and ads, using full data profile

This maturity model ensures you don’t over-invest too early but build capability as your teams and data evolve.

You could also have Sitecore Stream at the Crawl stage and learn how to use it before you start to walk or run! It can be super powerful.

Marketer Insight: You don’t have to go all-in at once. Start with a quick win, prove the value, and scale from there.

The Future: AI, Localisation, and Brand Empathy

The future isn’t about eliminating humans; it’s about elevating them. AI handles scale. Humans handle empathy, nuance, and judgement. Together, they enable brands to operate with speed and soul.

With Sitecore’s composable stack including XM Cloud, Personalize, CDP, and Stream; brands can move from disconnected silos to unified, multilingual customer experiences.

The real challenge isn’t just translating language, it’s localising meaning. True localisation means speaking to your customer in their language, yes, but also in their context, tone, and moment of need.

Article content
(image - DaLL-E)

 

Ready to Scale but also want a super Localisation strategy?

Our Sitecore Strategy MVP-led team helps enterprise brands:

·       audit localisation workflows,

·       evaluate readiness for CDP and Stream,

·       and design scalable, multilingual personalisation blueprints.

If you’re unsure where to begin or want to turn global ambition into real-world traction - get in touch. We’d love to help you build a roadmap that blends AI with human empathy.

To view or add a comment, sign in

Others also viewed

Explore topics