Traditionally, MSMEs in the Indian entrepreneurial landscape have always been the "economic workhorse," yet there has always been a "tech gap" with global powers. Now, a new paradigm is dawning and the migration of a conversational chatbot to an agentive AI process is set to equalise it for the first time.
In an exclusive conversation with FE Aspire, Vijayant Rai, Managing Director – India, Snowflake, discussed how generative AI is removing the need for specialised technical manpower and why a unified data foundation is the first step toward competing with the world. (Edited Excerpts)
Q. Indian MSMEs are just starting to move beyond basic AI tasks. How does the value proposition of "agentic AI" differ for a small business owner and why is now the right time to transition toward autonomous systems?
The transformation we are seeing is significant because generative AI puts power directly into the hands of the user. You no longer need a PhD or specialised engineering skills to leverage this technology. For MSMEs, the shift to agentic processes is a major differentiator. Traditionally, these businesses lacked access to the skilled technical manpower that larger corporations enjoy. Now, they can automate entire workflows and functions, such as HR or supply chain management, without needing specialised support. It allows them to bridge the talent gap and operate with a level of efficiency previously out of reach.
Q. You mentioned that users no longer need to be "tech-savvy" to benefit from these tools. How does this specifically change the way a founder interacts with their business data?
Exactly. It is not about everyone becoming tech-savvy but rather about technology becoming easy for everyone to use. In the past, if an MSME owner wanted to understand their business health, they had to build complex CEO dashboards and manually integrate parameters like supply and demand. Now, you can simply "talk to your data." In plain English, without knowing SQL or any technical language, you can create an agent to fetch information and build processes. It reduces the mental load on founders who already wear multiple hats.
Q. Many MSMEs struggle with data trapped in legacy systems or manual spreadsheets. What are the three essential steps a lean team should take to build a reliable data foundation?
First, you must break data silos. MSMEs often have multiple applications that do not talk to each other. Bringing everything onto a unified platform ensures governance and security. Second is context. You must embed business semantics into the AI, so it understands exactly what "revenue" or "customer" means for your specific industry to avoid hallucinations. Third is building governance and security into the design from day one. By unifying structured and unstructured data, such as videos and PDFs, businesses can solve efficiency challenges that were once impossible to address.
Q. Security and governance are often expensive. How does Snowflake ensure a mid-sized Indian firm has access to the same guardrails as a global enterprise without a massive IT budget?
Because Snowflake is a fully managed AI Data Cloud, the same level of security we provide to global banks is available to a small business in India. We handle compliance for frameworks like GDPR and India’s DPDP Act. For an individual company to build this level of security on its own would be nearly impossible. We take away the IT burden by managing the infrastructure in the background. The customer’s data remains their data, fully secured within the platform, and is never used to train public models.
Q. Can you share a real-world example of an Indian MSME using a modern data stack to "punch above its weight" and compete with much larger players?
Wakefit is a great example. They have built AI-driven solutions for customer experience and internal decision-making. In their showrooms, sales staff use a conversational interface to check inventory and pricing in real time, powered by agentic workflows. Another example is Dezerv in wealth management. They compete with massive institutions by delivering sharper, data-driven insights to relationship managers through a "Customer 360" view. These companies prove that with the right data platform, scale is no longer a constraint.
Q. In the current funding climate, does a robust AI and data strategy actually make an MSME more attractive to venture capitalists and global partners?
Absolutely. VCs look closely at the underlying technology stack. A platform like Snowflake provides assurance, security and trust. It tells investors that the business is built on a scalable foundation used by over 13,300 global customers. This builds immense credibility. It shows that the company is prepared for growth and that the leadership is focused on business outcomes rather than just managing messy IT infrastructure.
Q. Looking ahead, will agentic AI remain a niche tool or will it become the standard operating system for Indian businesses?
AI will become mainstream. India has already proven its ability to adopt data-driven systems at a national scale through Digital Public Infrastructure like UPI and Aadhaar. We see AI bringing that same large-scale impact to healthcare, agriculture and education. My message to MSME owners is that if you have the ambition, the technology is now simple, connected and trusted enough to help you realise it. By letting a platform manage the data layer, you can focus entirely on your customers and your growth.
