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Driving AI Adoption in Indian Enterprises
Prasanna, a former VC and one of the most trusted startup coaches in India, has mentored over a thousand founders in refining product-market fit and go-to-market execution.
The Indian startup ecosystem is at an interesting juncture. Artificial intelligence is transforming the perception of tech leaders toward solving challenges and ideas are flooding. However, ideas need strong backing to bear fruit. Upekkha, one of India's leading accelerators for Al-driven and Saasstartups, is at the heart of catering to this need by empowering founders to build capital-efficient, value-driven businesses from India for the global market. Upekkha was founded by Prasanna Krishnamoorthy, Shekhar Nair, and Thiyagarajan Maruthavanan, a trio with deep experience in venture building, product strategy, and global Al growth. The below interview with Prasanna—a former VC and one of the most trusted startup coaches in India—during Upekkha’s VIBE 2025 Summit in Bengaluru sheds light on the transforming AI ecosystem in the country.
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Upekkha is often referred to as the "Y Combinator of India." Can you briefly explain what Upekkha does and your focus over the last few years?
Absolutely. At Upekkha, we've worked with over 160 startups in the past eight years, and in just the last two, we've partnered with more than 50 AI startups, helping them go from zero to one. Change is happening rapidly in this space, and we strive to not only keep up but stay ahead.
In one of the earlier sessions, you mentioned a trend where Indian enterprises are slow to adopt AI. Why do you think this is happening?
One pattern we have noticed is that Indian enterprises haven’t been quick enough to adopt AI. There’s a mindset shift required when startups in India try to sell into these enterprises. It’s similar to when electricity was new—a hundred years ago, it was “magic.” But the problem with magic is that it is unreliable, and not something you could build on. But once electricity became a utility, the number of applications exploded. We’re seeing the same with AI: it’s moving from something magical and rare to a utility that anyone can tap into. The challenge is
to shift the mindset towards using AI as a utility. Relying on old ways of adopting technology just doesn’t work anymore.
How does this shift in mindset affect the adoption process for startups selling to enterprises?
Historically, for software in India, sales and adoption cycles have been painfully long—sometimes 18 to 24 months or more. To make a leap and become better adopters, Indian enterprises need to rethink how they trial and embrace new tools. Senior leaders need to witness firsthand the magic and speed that startups can bring. We’ve seen AI startups develop capabilities five or ten times faster than just a few years ago. Enterprises can benefit, but only if they're willing to be part of a process that involves experimentation, quick learning, and iterating while accepting some failures as part of the journey.
Bringing people together in person helps create a movement—a space where we start thinking about AI differently, aligned for the changes tomorrow will bring.
One standout is Tooth Lens. The founder is a dentist who wanted to enable more people to smile without invasive procedures. He developed a way to diagnose dental issues from photos. What’s unique is that the same technology now powers insurance, patient, and dentist applications. Star Health, for instance, launched India’s first dental OPD plan with Tooth Lens. When that happened, it created a ripple effect. Competitors suddenly felt they had to catch up, and now insurers are launching dental plans powered by this tech. It’s making dental insurance more affordable and accessible.
What needs to change for Indian enterprises and startups to truly lead in AI globally?
Startups are small and nimble, but lack the muscle to reach India’s massive population, let alone the world. We want senior enterprise leaders to experience what these startups can offer and realize how transformative they can be, given that there are proper guardrails and evaluation mechanisms in place. The goal is for Indian enterprises to excel not just domestically, but globally, leveraging AI to solve unique problems. Ideally, India could become the “use case capital” of the world for AI, with enterprises and startups working hand in hand.
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However, changing mindsets isn’t easy, especially when everyone’s dispersed. Bringing people together in person helps create a movement—a space where we start thinking about AI differently, aligned for the changes tomorrow will bring.
How do you see the challenge of adapting AI models to different geographies and value systems creating new opportunities for Indian talent?
If it is difficult to adapt an AI model built in India to the values and requirements of another country, that might actually be beneficial in some ways. This challenge means there will be ongoing demand for skilled professionals—AI developers, data scientists, and domain experts—to localize and adapt technology for different markets. Since India has the largest pool of such talent, we are well positioned to provide this expertise at scale across geographies. On the other hand, if one AI product can easily become globalized and fit perfectly everywhere, then the winner is less likely to be from here. Therefore, having unique requirements and values in each geography creates more opportunities for employment and continued innovation within our own ecosystem.
