Synopsis: Google is targeting India’s AI market by addressing the language gap, where only about 10% of the population speaks English, by building Gemini to support 29 Indian languages. With nearly 850 million active smartphones, this regional language focus helps Google reach users beyond cities and drive AI adoption in sectors like agriculture and healthcare.
Google is steadily strengthening its presence in India’s rapidly growing artificial intelligence (AI) market, aiming to tap into one of the largest and most diverse technology landscapes in the world.
With millions of new internet users coming online every year, a vast multilingual population, and an increasing demand for AI-driven products and services, India presents a unique opportunity for tech giants. Google is strategically adapting its AI offerings to meet local needs, from improving language support to tailoring services for Indian businesses and consumers, signaling its intent to become a major player in shaping the country’s AI future.
India’s Language Gap in AI
As artificial intelligence expands beyond English-speaking users, India has become a critical market for Big Tech companies. However, only about 10 percent of India’s population speaks English, while Indian languages make up less than 1 percent of open internet data. This creates a major gap for AI systems that are largely trained on English content. With seven of India’s top languages spoken by at least 50 million people, Google focuses on addressing this gap by building AI that can understand and operate in India’s regional languages.
India as a Global AI Testbed
AI models developed in India are not limited to the domestic market. Google has already exported agriculture-focused AI applications built in India to other parts of Asia and is expanding them into Africa. Google’s linguistic depth enables these models to adapt easily to other multilingual regions, demonstrating India’s role as both a market and a development base for global AI.
AI adoption is supported by India’s nearly 850 million active smartphones, according to IDC India. High smartphone penetration combined with regional-language AI enables Google to reach users far beyond English-speaking urban centers, targeting mass adoption in semi-urban and rural areas.
Building the Indic AI Ecosystem
Google’s work on Indic AI began with Project Vaani in December 2022, an open-source initiative to collect publicly accessible language datasets. This was followed by the launch of IndicGenBench, a benchmark to evaluate AI performance across 29 Indian languages. Google has also partnered with Bhashini, an initiative under India’s Ministry of Electronics and IT, and IISc Bengaluru to further fine-tune these models.
Global Competitiveness in Indic AI
Globally, Google’s Gemini 3 Pro is a strong contender in Indic-language AI. In benchmarks, it scored 59.9 out of 100, ranking second after Anthropic’s Claude Sonnet 4.5 at 60.7, while OpenAI’s GPT-5.2 scored 52.2, and xAI’s Grok 4 scored 52. These scores highlight Google’s competitive position in building AI that can understand and operate in Indian languages.
Embedding Indic Languages into Gemini
Google has embedded 29 Indic languages and dialects into Gemini, its foundational AI model. This involves training, fine-tuning and benchmarking the model’s performance across these languages. Currently, these language capabilities are available for text generation and translation, while commercial and pilot deployments depend on specific projects. According to Manish Gupta, senior director at Google DeepMind, this language proficiency is critical for last-mile applications such as agriculture and healthcare, where AI must interpret region-specific context to function properly.
Agriculture as a Key Entry Point
Agriculture is one of the most important areas where Google is deploying its Indic-language AI. Gemini powers an agricultural analysis model that operates in local languages, helping farmers with soil analysis, crop prediction and related insights. These services are delivered through partnerships with government and private sector entities, often at subsidised costs. Local language understanding allows the AI to interpret region-specific conditions and provide more accurate results.
Expanding AI Use in Healthcare
Google is also extending its AI strategy into healthcare by building multimodal AI systems. These models combine language capabilities with medical imaging to support healthcare delivery. A peer-reviewed paper on using Gemini 1.5 to detect diabetes through retina scans is scheduled to be published, highlighting how India is being used to develop and validate advanced healthcare AI solutions that can later be scaled. Manish Gupta emphasizes that native understanding of local languages is essential for scaling such applications across India’s diverse regions.
Balancing Scale with Ethics
Industry experts note that India’s linguistic diversity extends far beyond the 22 official languages, with 99 listed languages and more than 19,500 dialects. Ethical data collection and inclusion of smaller and script-less languages remain key challenges. Google has stated that it works with grassroots-level data providers to build Indic datasets, recognising the need for an equitable and community-driven approach.
Conclusion
By focusing on regional languages, government partnerships and high-impact sectors like agriculture and healthcare, Google is positioning itself strongly within India’s emerging AI market. Instead of building AI only for English-speaking users, the company is aligning its technology with India’s linguistic and social realities, laying the foundation for large-scale AI adoption across the country.
Written by Akshay Sanghavi
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