India's linguistic diversity is holding back its AI ambitions, warns Mint analysis

India's AI aspirations may be running into one of the country's oldest and most defining complexities: its staggering linguistic diversity. A sharp analysis in Mint argues that the country's hundreds of languages and dialects are complicating the diffusion of artificial intelligence, raising pointed questions about whether India's AI goals are effectively tongue-tied.

The core challenge is structural. The dominant AI language models — large language models that underpin chatbots, translation tools, coding assistants, and more — are trained overwhelmingly on English-language data. India has an estimated population of over a billion people, and a substantial majority communicates primarily in languages other than English: Hindi, Bengali, Tamil, Telugu, Marathi, and scores of others, many with limited digital text corpora for AI training.

This means that as AI begins to reshape how Indians access healthcare information, government services, education, and commerce, the benefits risk flowing disproportionately to the English-literate urban minority. For rural India and for speakers of smaller regional languages, AI could remain effectively inaccessible for years — creating a new dimension of digital inequality layered on top of existing ones.

The Mint piece comes at a moment when the Indian government has been actively promoting multilingual AI initiatives, including through platforms like BHASHINI. But building high-quality AI tools across even India's major scheduled languages requires data, investment, and time — and the gap between aspiration and reality remains wide. Without deliberate policy intervention, linguistic diversity could become one of India's most significant barriers to AI-led growth.