Even though the global AI hype is creating an ocean of funds, Indian investors are focused on the precious few droplets. In an exclusive interview with AIM, Vishnu Vardhan, founder & CEO of SML and Vizzhy, which is the creator of Hanooman, said that most Indian investors are not ready to spend money on research and deep tech startups. 

“Many VCs do not even have a thesis on how to invest in deep tech,” said Vardhan, referring to the country’s ill-informed deep tech investors. 

Citing Zepto, Dunzo, and other startups running without profits for investors for a long time, Vardhan said: “People are happy losing money there, but they don’t want to lose money here [AI startups],” he added.  

He also said India has created 125 unicorns, but nothing is great tech. “They are all business ideas and consumer apps,” he said.

Vardhan narrated a story about meeting a deep-tech investor who said his ticket size was only $2 million, which is minuscule compared to the investment required to do AI research. “I need at least INR 100 crore to set up a lab in India,” he added. 

Once, an investor asked Vardhan why he needed to set up a lab, talking about investing in the medical field. “Why don’t you treat 100 patients and tell me how much money you make?” the investor told Vardhan. After discussing it with his sister, Vardhan laughingly added that raising money in the US is better as Indian investors do not understand deep tech. 

How true is this?

Amit Sheth, the chair and founding director of the Artificial Intelligence Institute at the University of Southern Carolina (AIISC) also believes that there is a need for a lot more investment in AI in India compared to now. “VCs really don’t take as much risk as we expect/hope,” said Sheth.

“Most VCs do not understand the technology in-depth and don’t take risks with undeveloped markets where revenue and payoff are further off,” he added. “It is easy for them to understand consumer tech; most run after the fad and buy into the hype,” he added, while highlighting that big-tech companies like Microsoft or Google would be much happier to take the risk than VCs in India.

According to Rajan Anandan, managing director at Peak XV Partners, VCs are sitting on a total of $20 billion cash to invest in Indian startups, and the focus is currently on AI.

Arjun Rao, partner at Speciale Invest, which invests in deep tech startups, believes otherwise. “You could say there’s less investment when compared to Silicon Valley, but that is because Silicon Valley has much deeper pockets,” Rao told AIM, highlighting that VCs in India are only focused on investing in generative AI.

Rao explained that a lot of it is because there is not a concrete exit strategy when it comes to generative AI as the investment scenario is still just 1-2 years old in India. “India is still a young ecosystem. It is an unfair comparison,” said Rao. “We are moving at a very fast pace, which is the most important thing so we can catch up.”

Another great example is Khosla Ventures. The firm has invested in Upliance AI and Sarvam AI, two AI startups in India, and is bullish on AI globally. 

“We believe AI has the power to disrupt numerous economic models and change the way we lead our daily lives over the coming years. We invest in deep tech and invest where we can be early, bold and impactful,” believes Khosla Ventures.

It is also the startups’ fault

A few weeks ago, Gaurav Aggarwal, a former Google Research employee who is building an AI startup called Ananas Labs in India, put forth a similar opinion. He said that VCs are not ready to put money in deep-tech startups but are only interested in OpenAI wrappers and so-called consumer-tech startups. 

Arguably, Aggarwal’s point of view does make sense. India’s generative AI scene is on an upswing, but the investors are cautious when it comes to investing in research startups. Though India should also focus on foundational research, there should be investors willing to invest in deep-tech research as well, which is clearly not the case. 

Though it is rare to find any other initiative being built from scratch, the lack of VCs’ interest in such initiatives also shows a lack of understanding of the field, which, fortunately, is slowly changing as well. 

On the other hand, the investors are wary as well. There have been several early AI unicorns which have disappeared or are running dry with fundings. The fate of Jasper, Stability AI, or the very famous Instoried debacle, have made the VCs tread with caution. However, there is clearly a need for deeper pockets as well to invest in actual AI startups and take bigger risks.