IT Minister Ashwini Vaishnaw declared that as part of the ‘India AI Mission‘ to boost artificial intelligence (AI) infrastructure and skills, the government will set up more than 500 data laboratories across the country.
Speaking at a pre-event of the AI Impact Summit 2026, he added that this move is a component of the broader IndiaAI Mission, which has selected eight new firms to create large language models (LLMs), including Tech Mahindra, Fractal Analytics, and BharatGen, a consortium from IIT Bombay.
The team led by IIT Bombay has been given Rs 988.6 crore by the government through the IndiaAI Mission to create an LLM with one trillion parameters. Parameters are the internal variables of LLMs that draw linguistic correlations and patterns from training data.
The Center’s effort to create autonomous AI capabilities through sector-specific AI applications, GPUs, sovereign LLMs, and skill-building programs is known as the India AI Mission. At a cost of Rs 10,300 crore, it was approved earlier this year.
MeitY and the Office of the Principal Scientific Adviser will also unveil an AI framework in ten days, according to Vaishnaw.
Additionally, industry-specific small language models (SLMs) are being developed for weather forecasting, manufacturing, logistics, transportation, and agriculture.
The minister noted that Abhishek Singh, the CEO of the India AI Mission, has been directed to investigate adding 10,000 extra GPUs to the country’s present pool of 34,000.
Additionally, he emphasized the need for an international framework for AI governance, but cautioned that the realization of such an agreement may take some time.
The development of sovereign LLMs, or large language models trained on Indian datasets and languages, is a crucial part of the objective to reduce reliance on foreign AI systems.
In order to train and deploy large AI models, computational capacity is needed, and India currently has 34,000 GPUs allocated to the project.
The AI framework will be released to the public within the next 10 days, Vaishnaw said, with the first industry-specific language models concentrating on manufacturing, logistics, transportation, weather forecasting, and agriculture.