For years, much of Southeast Asia’s digital economy has been built around a quiet compromise: if users wanted access to the best technology, they often had to meet it in English. That bargain is beginning to shift.
New usage data around Google’s Gemini suggests that generative AI in the region is increasingly being used in local languages, not just by urban professionals writing emails or developers debugging code, but by farmers, older users, students, creators and small business owners who are more comfortable thinking, speaking and selling in their mother tongue.
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The clearest signal comes from Vietnam, where 89 per cent of Gemini prompts are now written in Vietnamese. Thailand is close behind, with 87 per cent of prompts in Thai, while Indonesia records 84 per cent in Indonesian.
The figures point to a deeper change in how AI is being adopted across Southeast Asia: usefulness is no longer simply about model size or speed, but about whether the system understands the language, idioms and cultural context of the person using it.
That matters in a region where English has long been treated as the default language of technology, even though it is not the default language of daily life for hundreds of millions of people.
The rise of native-language AI
The shift is not just anecdotal. The report cites the Southeast Asia Holistic Evaluation of Language Models, or SEA-HELM, a benchmark that assesses how large language models perform across regional languages. Gemini is ranked as the best-performing large language model overall for Southeast Asian languages in the evaluation, which covers Burmese, Filipino, Indonesian, Malay, Tamil, Thai, and Vietnamese.
For founders and developers, the implications are practical. A chatbot that works well in English may serve a bank’s urban customers, but it will not necessarily help a farmer in northern Vietnam, a shopkeeper in rural Thailand or a student in an Indonesian public school. To reach those users, AI products need to understand not only grammar and vocabulary, but also local phrasing, intent and cultural references.
This is where native-language performance becomes more than a technical milestone. It expands the addressable market for startups building education tools, financial services, health access platforms, customer support agents, creator tools and productivity apps. In a region as fragmented as Southeast Asia, language has often been a barrier to scale. Better multilingual AI could turn it into a distribution advantage.
Malaysia shows a slightly different pattern. English remains dominant for professional and coding-related tasks, reflecting the country’s multilingual workforce and its long-standing role as a regional services hub. But prompts in Malay have doubled in early 2026, according to the report. That suggests users are not abandoning English so much as switching languages depending on the task: English for work, Malay for learning, creativity or cultural expression.
A tea farmer and the economics of translation
The most compelling example in the source material comes from Lao Cai, a mountainous province in northern Vietnam known for its highland communities and ancient Shan Tuyet tea trees.
A small-scale tea farmer there once depended on middlemen to reach foreign buyers. The problem was not merely logistics; it was language. Selling premium tea to customers in Europe or the US requires more than listing weight and price. It involves storytelling, product descriptions, tasting notes, invoices and trust-building communication. Without fluent English, the farmer was stuck at the edge of the value chain.
Using Gemini, he can now describe his thoughts in Vietnamese and ask the AI to rewrite them in English “like an expert tasting a fine wine”. The output gives him polished descriptions that help position his tea for international buyers while preserving the authenticity of his own story.
This is a small example, but it captures why language-capable AI could matter for Southeast Asia’s small businesses. Translation has traditionally been treated as a support function. In practice, it can determine who captures value. If a farmer, craft producer, homestay owner or independent creator can communicate directly with global customers, they may keep more of the margin that previously went to intermediaries.
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For startups, this opens space for tools that combine AI translation with payments, logistics, compliance, product photography, storefront creation and customer relationship management. The opportunity is not simply to build another chatbot, but to help local businesses cross borders without losing their voice.
Culture is harder than vocabulary
Localisation is often described as a language problem. In Southeast Asia, it is also a cultural one.
In Malaysia, the report highlights marketing coordinators using Gemini in Malay to brainstorm visual concepts that capture the jiwa, or soul, of local culture. Terms such as lepak, referring loosely to the relaxed act of hanging out, or the familiar glow of kopitiam lighting, carry emotional weight that does not survive cleanly in literal English translation.
This distinction matters for the region’s creative economy. Southeast Asian brands increasingly want to participate in global digital culture without flattening their identity into generic international English. AI tools that understand local nuance could help agencies, content creators and small brands produce work that feels specific rather than templated.
It also matters for inclusion. In Thailand, the report notes that users over 54 are the most multimodal age group, using voice and image prompts in Thai to navigate daily tasks. That hints at another frontier for AI adoption: people who may not type comfortably, may not speak English, or may prefer to show the AI something rather than describe it.
In markets where ageing populations, rural connectivity gaps and uneven digital literacy remain real constraints, voice and image-based AI in local languages could be more transformative than text-only productivity tools aimed at office workers.
Rivals are racing for the same multilingual future
Gemini’s regional language performance puts Google in a strong position, but it is far from alone. OpenAI’s ChatGPT remains widely used across Southeast Asia, especially among English-speaking professionals, students and developers. Anthropic’s Claude has gained traction for writing and analysis-heavy workflows, while Meta’s open-source Llama models are attractive to developers and enterprises that want more control over deployment. Singapore’s AI Singapore has also developed SEA-LION, a family of language models focused on Southeast Asian contexts.
The contest will not be won only by benchmark scores. Distribution, pricing, developer tools, enterprise trust, government relationships and data governance will all matter. In Southeast Asia, one additional factor may prove decisive: whether the model can handle the region’s messy linguistic reality, where users mix English, local languages, dialects, slang and visual cues in the same conversation.
Why this matters for Southeast Asian startups
The Philippines remains an outlier in the Gemini report, with 90 per cent of prompts currently in English, the highest share in the region. That reflects the country’s strong English-language education base and its role in outsourcing, customer support and global services. But the broader direction is clear: the regional internet is becoming more multilingual, not less.
For startups, this changes product assumptions. Interfaces built only for English-speaking urban users will miss large segments of the market. Customer support bots will need to handle code-switching. Education apps will need to explain concepts in the language students use at home. Commerce platforms will need product descriptions that work across borders but begin in local speech.
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The bigger point is that AI adoption in Southeast Asia may not follow the same path as in the US or Europe. Here, the breakthrough use case may be less about replacing white-collar workflows and more about removing the language barriers that have kept millions of people from fully participating in the digital economy.
If generative AI can speak the language of the user’s home, it may become not just a productivity tool, but infrastructure for a more inclusive regional internet.
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