India’s linguistic heritage is among the richest in the world, with over 121 languages and 1,600 dialects. Yet, many Bharatiya Bhasha face significant challenges, including reduced usage in professional spheres, limited digital resources, and a declining rate of intergenerational transmission. In this era of digital transformation, language is a critical determinant of inclusive access to technology, education, and governance. Artificial Intelligence (AI) has emerged as a transformative tool to support and preserve these languages through advancements in Natural Language Processing (NLP), speech recognition, and machine translation.This paper examines how AI-driven initiatives, such as the government-backed Bhashini platform, are leveraging large-scale data collection to enable real-time translation and voice-based services in 22 scheduled languages. Key applications discussed include automated grammar correction, digitization of ancient manuscripts through Optical Character Recognition (OCR), and the creation of adaptive language-learning platforms that align with the National Education Policy (NEP) 2020.However, the path to a multilingual digital future is hindered by substantial barriers: scarcity of clean datasets for low-resource languages, inherent data biases, and the persistent rural-urban digital divide. Furthermore, the study addresses ethical considerations regarding cultural sensitivity and the risk of linguistic homogenization. By analyzing current technological trends and policy frameworks, this paper highlights future opportunities for sustainable linguistic development, arguing that a collaborative approach between developers, linguists, and policymakers is essential to ensure technology acts as a bridge rather than a barrier to India’s cultural heritage.
Chandraprakash D. Sanadi (Fri,) studied this question.