AI Summit and Awards 2026: Why India Is Not Behind in the AI Revolution

At the AI Summit and Awards 2026, Raghav Aggarwal (Co-founder at Fluid AI) took the stage to answer the question - ‘Can India build its own GPT’. He gives a great, in-depth and realistic look into this claim, by highlighting India’s challenges in the field of AI, the opportunities present and the direction Bharat should take to ultimately build its own GPT.

Here’s a brief lay down of what he covered in his session.

The ‘Indic Model’

Raghav highlighted how even Indian users today, primarily use global models like ChatGPT. The reason he claims, is the lack of pure Indic models being developed and adapted. However, he makes it clear that this scenario will change within 2-3 years, and India will have its own models. Raghav supports this claim by saying that India is a significant "data exporter," which is crucial for training data-hungry AI models.

This is where the ‘Indic Model’ concept comes in. An Indic model would be primarily trained on India-specific data and customized for Indian linguistic nuances and cultural context, including on information not publicly available on the global internet. This will ensure a deeper and more accurate understanding than global models, which often "collapse" when dealing with Indian specifics due to biases from Western-defined training data.

An example Raghav shares that best reflects this model, is the BHASHINI project, a government initiative actively working on digitizing historical data and collecting voice samples from authentic speakers to build this data foundation.

Challenges and Opportunities

The major challenge highlighted in the session was that India is currently an "interface industry" in AI, primarily using existing global models for business applications. However, he also states that the "interface" is as important as the model, as users primarily interact with the interface; the models can be switched at the backend. This makes India on par with the world in the AI revolution, which is compounded by its large number of engineers and understanding of software development.

India being a massive market and having a steady inflow of qualified professionals is why India has the potential to build its own GPT. Highlighting on the government’s role, Raghav explained that the government's role is to set up the "playground" through education systems and research and development. While many Indian talents contribute to global AI powerhouses, attracting and retaining this talent in India requires significant capital investment and incentives.

Building India’s GPT and its AI Future

The first step is to grow and attract the right talent, possibly with incentives. Capital comes second, which refers to the risk capital for foundational model development. Thirdly, there is also a need to implement appropriate and balanced regulation as well as be patient because building foundational models is a long-term (2-5 year, decadal) journey.

Additionally, Raghav also suggests focusing on innovative approaches like "reasoning models" rather than solely competing in the large language model (LLM) game.

Who is Raghav Aggarwal?

Raghav Aggarwal has always been an entrepreneurially and technologically driven man, which is evident from him co-founding Fluid AI in his early 20s while pursuing his MBA. Despite a formal background in finance, it’s his self-taught coding and AI development that made it possible. His brother and he have been recognised in Forbes’ 30 Under 30 (Asia) and Fortune’s 40 Under 40 lists, spotlighting them as leaders in technology and entrepreneurship.

His company Fluid AI focuses on building a no-code agentic layer that abstracts away the complexity of launching AI agents. Working with various models (global, Indian, open-source), it provides customers with an agentic platform for use cases like customer support and inventory management. Aggarwal also mentions creating an AI avatar of Warren Buffett that could answer questions based on his life's work, highlighting the democratizing potential of AI

In the end, Raghav makes it clear that AI is just an enabler, not a job killer. Be it helping smaller founders and teams achieve more, or scale operations, it can all be made easy using AI. He signs off by saying that AI is expected to permeate every industry, becoming a massive percentage of the real economy in the next 10-12 years.

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