THE rapid evolution of large language models has achieved grammatical correctness across major languages, yet this represents marketing inclusivity rather than true linguistic equality. While today’s AI can construct sentences in Tagalog, Swahili or Mongolian, the output remains inconsistent and inferior to English performance. Worse, the proliferation of wrapper applications without proper localization amplifies these deficiencies, potentially causing more harm than having no AI support at all.

Our experience building Egune AI in Mongolia revealed that perfect grammar is merely the starting point. The deeper challenge is not making AI speak every language; it is making AI think in every culture. When children grow up interacting with AI that fundamentally operates in English thought patterns, they gradually adopt linear, analytical reasoning, losing the circular, contextual cognition that characterizes many Asian and Indigenous languages. This represents cognitive homogenization disguised as technological progress.

The implications extend far beyond individual users. When governments process documents through foreign AI systems, health care providers rely on AI trained on different medical traditions, and educational institutions deploy AI that misunderstands local pedagogical approaches, entire nations become digitally dependent. They participate in the AI revolution as data providers rather than value creators, feeding sensitive information into systems that extract economic benefit without proportional return.

Digital sovereignty has become essential for nations serious about their technological future. This transcends data localization requirements, though those are important. It is about controlling the AI systems that increasingly mediate citizen interactions with essential services. When critical infrastructure depends on foreign entities subject to external laws and priorities, true independence becomes impossible.

Building AI for languages with limited digital presence requires fundamental rethinking. Mongolian, spoken by three million people, represents less than 0.01 percent of internet content. Web scraping yields mostly translated content reflecting foreign thought patterns rather than authentic expression. We discovered that a million translated sentences teach less about genuine Mongolian thinking than a thousand authentic native conversations.

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Our solution involved building dedicated data teams to create quality datasets. We digitized books, transcribed audio and video content, collected academic writing, and manually cleaned and corrected everything. While major AI systems train on trillions of tokens of varying quality, we focused on millions of carefully curated, culturally authentic examples. Every piece underwent native-speaker verification for natural expression. This approach took longer and cost more, but the results justified the investment: our AI understands not just Mongolian words but Mongolian thinking patterns.

Sovereign AI development enables capabilities impossible with foreign systems. During Mongolia’s harsh winters, we immediately update models with emergency protocols. When legislation changes, government agencies integrate updates within days rather than months. This agility becomes impossible when dependent on global release cycles prioritizing larger markets.

Local development ensures consistent alignment with national priorities. Security vulnerabilities specific to local infrastructure receive immediate attention. Critical bugs affecting local users receive priority treatment rather than languishing in global backlogs. Most importantly, economic value from AI development remains domestic, creating jobs and building expertise rather than extracting value abroad.

Our recent launch of Egune Chat on iOS and Android platforms demonstrates practical sovereign AI implementation. Users select their geographic region, accessing AI trained on specific cultural and administrative contexts. Rural Mongolians receive responses that consider traditional practices and limited infrastructure. Urban professionals get advice relevant to modern city resources. This is not translation; it is fundamentally different training for different realities.

The platform now serves more than 50,000 daily users experiencing qualitative differences from generic global systems. Government agencies process sensitive documents without international data exposure. Banks serve customers using locally appropriate financial concepts. Health care providers offer consultation grounded in available resources and local medical practices.

Building national AI capabilities no longer requires competing with trillion-parameter models. Focused, culturally optimized systems serve specific populations better than generic global solutions while requiring a fraction of the resources. A $50 million investment in sovereign AI creates more local value than $500 million spent on foreign AI subscriptions.

International collaboration need not conflict with digital sovereignty. Nations can share open-source frameworks and methodologies while maintaining control over implementations. Mongolia’s experience can inform efforts in the Philippines, while Filipino innovations in multi-dialect processing might benefit Indonesia. This creates a network of diverse, interoperable AI systems rather than monolithic global platforms.

The future of inclusive AI requires recognizing that each culture offers unique problem-solving patterns worth preserving in the digital age. True inclusivity demands AI systems that understand local context, respect sovereignty, and serve actual population needs rather than assuming universal solutions exist.

From Mongolia, we have demonstrated that nations can build world-class AI while maintaining cultural authenticity and digital independence. The technology exists, the economics work, and the benefits are clear. The question for other nations is not whether to pursue sovereign AI but how quickly they can begin. In a world where AI increasingly mediates human activity, the choice is simple: build your own capabilities or accept permanent digital dependence.

Badral Sanlig is a Mongolian technology entrepreneur and AI practitioner best known as the founder and chief executive of Egune AI, a Mongolia-based artificial intelligence company focused on sovereign, culturally grounded AI systems.