Can AI understand Malay, Mandarin and Manglish? What it means for your business online

Yes, but unevenly. ChatGPT, Gemini and Google's AI Overviews now understand Malay, Mandarin and mixed Manglish far better than a year ago, and Google added Malay to AI Overviews in 2025 (Google, 2025). The catch: their answers in these languages are only as good as the clear local content they can find, and for most Malaysian businesses that content does not exist yet.

Key takeaways

• Malaysians search in Malay, English, Mandarin and mixed "Manglish", and AI assistants must handle all of it. Google's AI Overviews now run in over 40 languages, with Malay added in 2025 (Google, 2025).
• The reach is real. Malaysia has 35.4 million internet users at 98.0 percent penetration (DataReportal, 2026), and ChatGPT alone serves over 800 million people a week (OpenAI, 2025).
• AI handles non-English well but imperfectly, because the web it learned from is mostly English. English is the content language of 49.7 percent of all websites (W3Techs, 2026), so the Malay and Mandarin answer space is thin and open.
• That gap is your opportunity. Few local businesses publish clear, answer-first content in the languages their customers use, so the AI has little to recommend and the field is wide open.
• The fix is answer engine optimization (AEO): publish clear answers in each language your customers use, keep your core facts identical across them, and never rely on auto-translation alone.

Can ChatGPT, Gemini and Google AI actually understand Malay, Mandarin and Manglish?

Yes, and increasingly well. The big assistants are multilingual by design and handle Malay, Mandarin and even mixed "Manglish" queries. Google added Malay to AI Overviews in 2025, alongside Chinese and Arabic (Google, 2025). The honest limit: comprehension is strong, but the quality of the answer still depends on the local content the AI can find in that language.

Here is the mechanism. A model understands a question in Malay or Mandarin, then composes an answer from what it has learned and the sources it trusts. If clear, factual Malay or Chinese content about your industry exists, the AI uses it. If it does not, the model leans on translated English sources or, worse, on a competitor who did publish in that language. Understanding the question was never the hard part. Having something trustworthy to answer with is.

Google was explicit about the rollout. In its own words, "AI Overviews are now available in more than 200 countries and territories and in more than 40 languages," with "support added for Arabic, Chinese, Malay, Urdu and more" (Google, 2025). For a Malaysian SME, that single line means your Malay-speaking and Mandarin-speaking customers are already getting AI answers about your industry. The only question is whose name appears in them.

How do Malaysians actually search, and in which language?

In a mix, and they switch without thinking. A Klang Valley buyer might type a Malay phrase, a Mandarin term and an English brand name in the same week, often blending them inside one query. With 35.4 million internet users and 98.0 percent penetration (DataReportal, 2026), that messy, multilingual search behaviour is the norm, not the exception.

Malaysia is genuinely multilingual online. English proficiency is high. Malaysia scores 581 on the EF English Proficiency Index and sits in the "high proficiency" band, ranked 24th in the world (EF, 2025). So many Malaysians search comfortably in English. But plenty also search in Bahasa Melayu for everyday services, and the Chinese-speaking community searches in Mandarin for the same. Three live search languages, one small country.

Then there is Manglish, the natural code-switching where a query mixes English with Malay or Chinese words and local slang. People do not write "professional accounting services Petaling Jaya"; they write the way they speak. Modern AI assistants are far better at parsing this than the old keyword-matching search box, because they read for meaning rather than exact words. That is good news for the customer. It is also why a business that only ever published stiff, formal English copy can still be missed: the AI understood the casual Malay-English question perfectly, but found nothing local and human to match it to.

Why is multilingual AI search an opportunity for Malaysian businesses?

Because almost nobody local has filled the space. AI assistants want clear, trustworthy content in the language of the question, and very few Malaysian SMEs publish answer-first content in Malay or Mandarin. The answer space in those languages is wide open, so the first business to fill it well can own the recommendation.

The structural reason is the data the models learned from. English is the content language of 49.7 percent of all websites, far ahead of any other language (W3Techs, 2026). So the web is lopsided toward English, which means the Malay and Mandarin "shelves" the AI reaches for are comparatively bare. When a shelf is bare, the first credible item placed on it gets picked again and again.

This is not a small or shrinking channel. Traffic to retail sites from generative-AI sources rose more than 1,300 percent over the 2024 year-end season compared with a year earlier (Adobe Analytics, 2025). And the content tactics that win are measured, not guessed. The first peer-reviewed study on the subject found:

"Through rigorous evaluation, we demonstrate that GEO can boost visibility by up to 40% in generative engine responses." Aggarwal et al., the Princeton GEO study (ACM KDD 2024).

In plain terms, content that states facts clearly, adds real statistics and quotes credible sources gets pulled into AI answers far more often. Do that in Malay and Mandarin, where your competitors have not, and the gap is yours to take. For the full picture of why a business stays invisible to AI, see our guide on why your business does not show up in ChatGPT or Google AI.

What should a business do about multilingual AI search? (per-language tactics)

Publish clear, answer-first content in each language your customers actually use, keep your core facts identical across every language, and never rely on machine translation alone. The goal is simple: whichever language the customer asks in, the AI finds a clear, consistent, human answer about your business and recommends you by name.

The table below sets out the tactics, language by language, plus the rules that apply across all of them.

Two cross-cutting rules decide whether this works. First, consistency of facts. Your business name, services, location and phone number must be identical in every language, because conflicting information makes an AI less confident and more likely to name someone else. Second, no auto-translation alone. Machine translation is a useful first draft, but raw output reads unnaturally, mistranslates industry terms and signals low quality to both customers and AI. Have a fluent human review anything customer-facing.

Does auto-translation hurt my AI visibility?

On its own, yes, it can. A page of raw machine-translated text often misuses industry terms, reads awkwardly to a native speaker and gives the AI a weaker, less trustworthy source to quote. Auto-translation is fine as a starting draft. It is not fine as the final answer your Malay or Mandarin customers and the AI both rely on.

The deeper issue is trust. AI assistants favour content they can understand clearly and verify confidently, the same way they favour businesses with consistent facts and real third-party mentions. Awkward, clearly machine-made copy reads as lower quality, so it is less likely to be the source the AI repeats. You can have perfectly accurate facts and still lose, simply because the writing signals "do not trust me".

So treat each language as real content, not a checkbox. Draft with whatever tools help, then have a fluent person make it natural, correct the terminology and keep the facts aligned with your other languages. That single step lifts both the customer experience and the odds that an AI quotes you. It also compounds: the more clearly and consistently you describe your business across languages, the safer every assistant feels naming you.

Acclaira runs a free AI-visibility check for Malaysian businesses. We ask ChatGPT, Gemini and Google the questions your customers ask, in the languages they ask them, then show you whether the answer names you or a competitor and hand you the single highest-impact fix. It costs nothing and it is the fastest way to see where you stand. You can explore the approach on our AI-search and AEO service page, or read more guides in our Insights library.

When your customer asks AI who to trust, you want one name to come back. Make it yours. Be the answer.

Sources

• Google, May 2025, AI Overviews expansion to 200+ countries and 40+ languages (Malay added): https://blog.google/products/search/ai-overview-expansion-may-2025-update/
• DataReportal, Digital 2026 Malaysia: https://datareportal.com/reports/digital-2026-malaysia
• EF English Proficiency Index, Malaysia: https://www.ef.com/wwen/epi/regions/asia/malaysia/
• W3Techs, Usage statistics of content languages for websites: https://w3techs.com/technologies/overview/content_language
• Aggarwal et al., GEO: Generative Engine Optimization, Princeton (ACM KDD 2024): https://arxiv.org/abs/2311.09735
• OpenAI via TechCrunch, October 2025, ChatGPT at 800 million weekly users: https://techcrunch.com/2025/10/06/sam-altman-says-chatgpt-has-hit-800m-weekly-active-users/
• Adobe Analytics, 2025, generative AI traffic to retail sites: https://blog.adobe.com/en/publish/2025/03/17/adobe-analytics-traffic-to-us-retail-websites-from-generative-ai-sources-jumps-1200-percent