AI as the Next Global Battleground: Rajeev Chandrasekhar on Geopolitical Posturing and India’s AI Strategy

India Ramps Up AI Adoption but Faces Tough Competition from China and the US

Artificial Intelligence (AI) is poised to become the most critical battleground of the future, triggering intense geopolitical maneuvering for control and access to AI technologies, according to Rajeev Chandrasekhar, Former Minister of State for Electronics and IT. Speaking at the Mumbai Tech Week on February 28, 2025, Chandrasekhar emphasized the importance of India developing deep AI capabilities to remain competitive in the evolving technological landscape.

“AI is the next battleground of the future, and there is going to be a lot of geopolitical posturing around access to AI,” he stated. “It is very, very important for countries to create deep capabilities in AI, just as it is for semiconductors.”

AI as a Strategic Asset: The Push for ‘Sovereign AI’

Chandrasekhar stressed the importance of developing indigenous AI models, sometimes referred to as “Sovereign AI”, where nations have full control over their data, foundational models, and AI infrastructure.

“Whether you want to call it Sovereign AI or focus on foundational models and expert AI systems, having deep AI capabilities is as important as developing semiconductor technology,” he added.

This comes as India’s IndiaAI Mission is gaining traction, with the government earmarking ₹1,500 crore to support indigenous AI model development. The initiative, led by the Ministry of Electronics and IT (MeitY), aims to back Indian startups and researchers in developing foundational AI models and infrastructure.

Can India Catch Up? The AI Race Against the US and China

A key question surrounding India’s AI ambitions is whether it can compete with AI superpowers like the US and China, who have been investing in AI research and development for over a decade.

Union IT Minister Ashwini Vaishnaw recently stated that India has at least six major AI developers who could launch large language models (LLMs) within six to eight months.

However, Chandrasekhar cautioned against setting rigid timelines in such a fast-evolving field:

“In this game, neither the timelines nor any roadmap will hold true… What the government is doing is really to catalyze the AI ecosystem.”

He acknowledged that while India has accelerated AI adoption, it still lags behind China and the US in AI capabilities and foundational research.

“We are a bit behind China and the US, and we have to play catch-up. But these are early days in AI—it’s like a race with 20 heats, and we are only in the first heat. There are many more to go before winners or losers are decided,” Chandrasekhar explained.

US and China: The AI Heavyweights Leading the Global Race

Since late 2022, US technology giants like OpenAI, Google, Microsoft, and Anthropic have dominated the AI space, investing billions of dollars into generative AI models.

For a long time, the US was considered the undisputed leader in AI, thanks to its vast resources, high-performance computing (HPC) capabilities, and deep AI talent pool. However, China has recently challenged this notion.

One striking example is Chinese AI startup DeepSeek, which launched its large language model (LLM) with an investment of just $5.6 million and 2,000 GPUs—a fraction of the resources required by OpenAI’s GPT-4o, which cost $100 million to train.

This indicates that AI development is no longer restricted to companies with billion-dollar budgets, and nations with strategic planning, talent, and efficient computing can still compete globally.

India’s AI Strategy: Key Initiatives & Challenges

India is taking major steps to position itself as a global AI player, focusing on:

• Developing indigenous AI models through the IndiaAI Mission.
• Encouraging AI research in universities and startups with government funding.
• Expanding AI infrastructure, including the establishment of supercomputing centers for AI model training.
• Partnering with global AI leaders to facilitate knowledge-sharing and accelerate AI adoption.

However, India faces key challenges in achieving global AI leadership:

1. Limited AI Compute Power – Unlike the US and China, India lacks large-scale GPU clusters and AI supercomputing resources necessary for training large AI models.
2. AI Talent Gap – While India has top AI engineers, many migrate to Silicon Valley or China for better opportunities.
3. Data Availability & Regulations – Privacy concerns and regulatory restrictions can limit access to diverse high-quality datasets for AI training.
4. Funding Constraints – AI research requires massive investments, and private sector participation is still growing in India.

The Road Ahead: India’s AI Potential

Despite these challenges, India has strong AI adoption rates, a growing digital economy, and a large pool of AI talent, making it well-positioned to become a global AI hub in the coming years.

Chandrasekhar remains optimistic about India’s ability to develop deep AI capabilities, emphasizing that the AI race is still in its early stages.

“We are now showing up, and we are building these deep AI capabilities even as AI adoption continues to accelerate,” he concluded.

AI as a National Priority

As AI reshapes industries, economies, and global power structures, India must prioritize AI investments, research, and infrastructure to remain competitive. With government-backed initiatives like the IndiaAI Mission, strategic public-private partnerships, and a focus on indigenous AI models, India is laying the groundwork for an AI-driven future.

However, to truly compete with AI giants like the US and China, India needs to significantly boost its AI computing power, talent development, and investment ecosystem. The next few years will be crucial in determining whether India emerges as a global AI leader or continues playing catch-up in the AI revolution.