Tech Mahindra says India needs to shift from consumption to production to be self-reliant with AI

The India AI Impact Summit 2026 was pretty interesting, and many startups showcased innovations in a lot of different sectors. Though it also helped us understand the bigger picture, and that is, how exactly is India looking at becoming self-reliant in AI? 

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I got an opportunity to speak with Nikhil Malhotra, from Tech Mahindra, who is the Chief Innovation Officer and the Global Head of AI at the company, and had an insightful conversation with him. He suggests that while India is already self-reliant to a large extent, the next phase of growth requires a massive shift in how the country engages with technology. 

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As per him, right now India operates on a consumption economy in the AI space, but in order to reach true self-reliance, the country will have to transition into a production-based system. Let’s take a look at everything I gathered from our conversation.

Also Read: Tata’s vision for an AI-powered India at the India AI Impact Summit 2026

True definition of becoming self-reliant 

First of all, Nikhil emphasised the true definition of becoming self-reliant with AI. According to him, self-reliance is not just about using AI tools but about possessing two specific capabilities, which include having infrastructure and control over the AI algorithm. 

He suggests that having the infrastructure is the most important thing that is required in order to support AI development. Not only that, but he also said that it is important to have the ability to control the algorithms and the models that are being produced and used across the country.

Here’s what he said, “To a large extent, India is self-reliant at this point of time. And we are increasing that capacity. I think when we have our own infra and we have the ability to control the algorithms on the models in terms of what we do and what we produce.”

What is Tech Mahindra doing in the space?

Moving further, Nikhil also explained what exactly Tech Mahindra is doing in the space. He explained that they’ve been working on their Project Indus, which serves as a primary example of the production mindset that he suggested. 

As per him, the main reason behind working on this project was because of the challenge issued by Sam Altman in 2023 regarding whether India could build an LLM from the ground up, or not. Unlike many models that build upon existing foundations, he said that they did not use any external frameworks like Llama, Cohere, or ChatGPT.

He gave a further deep dive and explained that the model was built with 1.2 billion parameters. Not only that, but the production effort has now been integrated into the India AI Mission. He said that the company is currently developing a bunch of LLMs specifically for education. They even had one of these LLMs at their booth, which was being shown to the public.

Also Read: AIONOS CTO on building AI stack for enterprises at the India AI Impact Summit 2026

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Madhav Banka

Madhav works as a consultant at Digit, covering branded content and feature stories. He has been a part of the consumer tech industry for over 4 years, covering news, features & reviews. While not busy working, you'll usually find him roaming around Delhi in hopes of getting good pictures, playing video games or watching films and F1 during weekends. View Full Profile