India has 22 officially recognised languages and over 19,500 dialects. Its digital economy, however, has been built almost entirely in English — creating a structural accessibility gap that affects hundreds of millions of people who transact, work, and communicate in their mother tongue. That gap is now closing fast.

In 2025, Sarvam AI released IndicVoice — a speech recognition model trained on over 5,000 hours of audio data across 10 Indian languages. Krutrim launched a multilingual LLM that outperforms GPT-4 on Hindi, Bengali, and Tamil benchmarks. The government's Bhashini platform enables real-time translation across 22 languages.

For Indian enterprises with mass-market ambitions, language is not a localisation feature. It is a fundamental capability. The international infrastructure for multilingual AI is maturing rapidly — and Indian enterprises that don't build vernacular capability into their AI strategy will find themselves behind both global peers and domestic competitors who do.