India has long been seen as a powerhouse of technological talent, but when it comes to artificial intelligence (AI), the nation has struggled to keep pace with global leaders. While OpenAI, Anthropic, Deepseek, Qwen, and other AI giants have made significant advances, India’s AI landscape has remained relatively nascent. That is, until now. Ola’s Bhavish Aggarwal has set his sights on changing that narrative with Krutrim, his ambitious AI venture.
The Big Bet on AI
Ola’s AI subsidiary, Krutrim, has announced an initial investment of ₹2,000 crore, with plans to scale up to ₹10,000 crore by next year. This will fuel the launch of an AI lab, Krutrim 2 (an advanced large language model), and several AI-driven applications spanning vision, speech, and translation. Krutrim also aims to democratize access to Nvidia’s GB200 chips via its cloud platform, making it one of the first to bring cutting-edge AI hardware to India.
While the ambition is commendable, the question remains: is India arriving at the AI race too late?
The Global AI Gap
Krutrim’s efforts, while significant, must be viewed in the broader context of the global AI arms race. OpenAI has received billions in funding from Microsoft, while China’s Deepseek has demonstrated remarkable efficiency, despite limited access to U.S. chips. In contrast, Krutrim’s ₹2,000 crore (~$230 million) investment pales in comparison to the tens of billions poured into AI development globally.
Another challenge is India’s lack of foundational AI infrastructure. While Krutrim aims to build India’s largest supercomputer by year-end, OpenAI and Google DeepMind already have vast computational resources at their disposal. The effort is commendable, but whether it will be enough to compete with the world’s AI leaders is uncertain.
The India Advantage: Localized AI and Open Source Potential
Despite its late entry, Krutrim has some strategic advantages. Aggarwal has positioned Krutrim as an AI for India, focusing on Indian languages, cultural context, and accessibility—an area where Western AI models often fall short. By prioritizing multilingual capabilities across Hindi, Bengali, Telugu, Tamil, Marathi, and other Indian languages, Krutrim has a niche market to dominate.
Additionally, Krutrim has open-sourced parts of its AI stack, a move that could accelerate innovation in India’s AI ecosystem. If developers and enterprises build on Krutrim’s AI models, India could carve out a unique position in the global AI value chain—leveraging its large pool of engineers and startups.
The Road Ahead: Challenges and Opportunities
To truly be competitive, Krutrim must scale quickly and efficiently. Some critical factors to watch:
- Infrastructure & Compute Power – Can Krutrim’s planned 1 GW data center expansion by 2028 provide enough computing power for AI breakthroughs?
- Talent & Research Ecosystem – Will India’s AI researchers and developers rally around Krutrim, or will they continue to migrate to Silicon Valley and Chinese firms?
- Regulatory & Funding Landscape – AI requires deep capital reserves. Will Indian investors and policymakers provide sustained support, or will this remain a fragmented effort?
- Product-Market Fit – Can Krutrim’s AI solutions find real-world applications that make them indispensable, beyond just being an Indian alternative to global models?
A Promising Start, But More is Needed
Krutrim’s launch is a much-needed step in India’s AI journey, but it is only the beginning. While the investment is significant by Indian standards, it is a fraction of what global players are spending. Without aggressive scaling, India risks becoming a perpetual follower in AI rather than a leader.
However, if executed well, Krutrim could jumpstart India’s AI ecosystem, create a robust foundation for AI innovation, and ensure that the country is not merely a consumer but also a creator of AI technologies. The world’s AI race is far from over—India still has a chance to shape the future, but the clock is ticking.
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