From data migration to AI agents: Why Snowflake is betting big on India
AI Data Cloud firm says India is one of its fastest-growing markets globally as enterprises accelerate AI adoption, migrate legacy data systems and experiment with agentic AI at scale.
- Jun 5, 2026,
- Updated Jun 5, 2026 10:03 AM IST
Artificial intelligence (AI) is reshaping how enterprises manage data, build software and run operations, and cloud data company Snowflake is betting that India will be one of the biggest beneficiaries of that shift.
“India is one of the fastest growing markets for Snowflake globally,” Sridhar Ramaswamy, chief executive officer of Snowflake, told Business Today, as enterprises increasingly move away from siloed legacy systems towards unified data and AI platforms.
The Nasdaq-listed company, which reported revenue of $4.68 billion, has doubled its India headcount to about 700 employees over the past two years. The country has emerged as a key strategic market for Snowflake, not only because of rising adoption among local enterprises but also due to the growing role of India's global capability centres (GCCs) and development hubs in driving AI initiatives for multinational corporations.
Snowflake works with customers including Indigo, Swiggy and Bajaj Allianz General Insurance, while also supporting a large ecosystem of partners serving both Indian and global markets. Around half of Snowflake’s Asia-Pacific and Japan partner ecosystem, including firms such as Microsoft, TCS and Deloitte, is based in India.
The company’s development centres in Pune and Bengaluru support global operations across functions, including engineering, finance and IT. Increasingly, they are also becoming hubs for AI-led innovation.
According to Ramaswamy, much of the momentum is being driven by the emergence of agentic AI.
“Agentic AI is opening up new areas of growth as companies turn to AI to simplify processes and improve data management,” he said.
Snowflake has seen a sharp spike in customer uptake for its core AI offerings, Snowflake CoCo, an agentic coding assistant, and Snowflake CoWork, an intelligence platform. Both have seen rapid deployment across enterprises in recent months as companies seek to reduce costs and accelerate technology projects.
Ramaswamy said AI is dramatically changing the economics of software development and data management. Processes such as data migration that previously required hundreds of employees working over long timelines can now be completed with significantly smaller teams and in a fraction of the time.
At Snowflake itself, AI tools are increasingly being used internally to automate routine work and free employees to build new applications. Much of that work is being driven from the company’s Pune centre.
One such example is Snowflake’s GTM AI Assistant, which is used by more than 6,000 employees to track external engagement and personalise communication strategies. The company said its demand-generation teams have achieved a 99.9% accuracy rate in enhanced lead filtering, sharply reducing spam and fake leads entering internal databases.
The AI push comes as Snowflake deepens its partnerships with major technology providers to support growing enterprise demand. In recent days, the company announced a $6 billion multi-year infrastructure commitment with Amazon Web Services and a strategic partnership with Anthropic, underscoring the scale of AI and data workloads moving onto its platform.
The demand is already visible in customer adoption. According to Ramaswamy, 13,600 of Snowflake’s 13,900 customers now use its agentic AI capabilities on a weekly basis.
“We are seeing AI acceleration at scale across India,” said Vijayant Rai, managing director of Snowflake India.
“One part of what we do here is what we build from India with ISVs and partners who are building assets on top of Snowflake,” Rai said.
Beyond enterprise adoption, Snowflake is also investing in AI skills development. The company has committed $20 million globally to help upskill one million people in data and AI by 2029. In India, it is working through initiatives such as FutureSkills Prime alongside Nasscom and MeitY, as well as with the ICT Academy to train professionals and educators.
Ramaswamy believes the widespread adoption of AI agents will force enterprises to rethink traditional business models, particularly in consulting and software services, where pricing is increasingly shifting from effort-based engagements to outcome-based models.
For employees, the implications could be equally significant.
“A single person can now create a product specification, implement it and also do deep research on the competition,” Ramaswamy said.
As AI tools become more capable, he expects professionals to evolve from narrow specialists into broader generalists who can use AI to amplify productivity across multiple functions.
Despite growing competition in enterprise AI, Snowflake remains bullish on India’s long-term potential.
“India is a massive opportunity waiting to happen,” Ramaswamy said. “From traditional enterprises that are keen to adopt AI and moving to production use cases on Snowflake and the mix of digital natives and traditional enterprises working on migrating their data, demand is only increasing.”
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Artificial intelligence (AI) is reshaping how enterprises manage data, build software and run operations, and cloud data company Snowflake is betting that India will be one of the biggest beneficiaries of that shift.
“India is one of the fastest growing markets for Snowflake globally,” Sridhar Ramaswamy, chief executive officer of Snowflake, told Business Today, as enterprises increasingly move away from siloed legacy systems towards unified data and AI platforms.
The Nasdaq-listed company, which reported revenue of $4.68 billion, has doubled its India headcount to about 700 employees over the past two years. The country has emerged as a key strategic market for Snowflake, not only because of rising adoption among local enterprises but also due to the growing role of India's global capability centres (GCCs) and development hubs in driving AI initiatives for multinational corporations.
Snowflake works with customers including Indigo, Swiggy and Bajaj Allianz General Insurance, while also supporting a large ecosystem of partners serving both Indian and global markets. Around half of Snowflake’s Asia-Pacific and Japan partner ecosystem, including firms such as Microsoft, TCS and Deloitte, is based in India.
The company’s development centres in Pune and Bengaluru support global operations across functions, including engineering, finance and IT. Increasingly, they are also becoming hubs for AI-led innovation.
According to Ramaswamy, much of the momentum is being driven by the emergence of agentic AI.
“Agentic AI is opening up new areas of growth as companies turn to AI to simplify processes and improve data management,” he said.
Snowflake has seen a sharp spike in customer uptake for its core AI offerings, Snowflake CoCo, an agentic coding assistant, and Snowflake CoWork, an intelligence platform. Both have seen rapid deployment across enterprises in recent months as companies seek to reduce costs and accelerate technology projects.
Ramaswamy said AI is dramatically changing the economics of software development and data management. Processes such as data migration that previously required hundreds of employees working over long timelines can now be completed with significantly smaller teams and in a fraction of the time.
At Snowflake itself, AI tools are increasingly being used internally to automate routine work and free employees to build new applications. Much of that work is being driven from the company’s Pune centre.
One such example is Snowflake’s GTM AI Assistant, which is used by more than 6,000 employees to track external engagement and personalise communication strategies. The company said its demand-generation teams have achieved a 99.9% accuracy rate in enhanced lead filtering, sharply reducing spam and fake leads entering internal databases.
The AI push comes as Snowflake deepens its partnerships with major technology providers to support growing enterprise demand. In recent days, the company announced a $6 billion multi-year infrastructure commitment with Amazon Web Services and a strategic partnership with Anthropic, underscoring the scale of AI and data workloads moving onto its platform.
The demand is already visible in customer adoption. According to Ramaswamy, 13,600 of Snowflake’s 13,900 customers now use its agentic AI capabilities on a weekly basis.
“We are seeing AI acceleration at scale across India,” said Vijayant Rai, managing director of Snowflake India.
“One part of what we do here is what we build from India with ISVs and partners who are building assets on top of Snowflake,” Rai said.
Beyond enterprise adoption, Snowflake is also investing in AI skills development. The company has committed $20 million globally to help upskill one million people in data and AI by 2029. In India, it is working through initiatives such as FutureSkills Prime alongside Nasscom and MeitY, as well as with the ICT Academy to train professionals and educators.
Ramaswamy believes the widespread adoption of AI agents will force enterprises to rethink traditional business models, particularly in consulting and software services, where pricing is increasingly shifting from effort-based engagements to outcome-based models.
For employees, the implications could be equally significant.
“A single person can now create a product specification, implement it and also do deep research on the competition,” Ramaswamy said.
As AI tools become more capable, he expects professionals to evolve from narrow specialists into broader generalists who can use AI to amplify productivity across multiple functions.
Despite growing competition in enterprise AI, Snowflake remains bullish on India’s long-term potential.
“India is a massive opportunity waiting to happen,” Ramaswamy said. “From traditional enterprises that are keen to adopt AI and moving to production use cases on Snowflake and the mix of digital natives and traditional enterprises working on migrating their data, demand is only increasing.”
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