In India, the number of VCs and angel investors that are getting interested in AI startups is skyrocketing. It is often believed that most of them don’t even have a thesis while investing in these startups, but the same goes for several startups that are innovating, or at least hoping to, in the space.

Most of the Indian AI startups are powered by Jugaad, not VC money, which makes it harder for them to put those funds into R&D. Instead, they focus on the North Star Metric, often called the valuation, and bringing profitability earlier for their investors, giving them an exit.

But this hampers what Indian startups can achieve if given enough money and time to focus on R&D. At the same time, VCs are hesitant to invest in startups that are focusing too much on R&D, as it would take a lot of time for the company to even reach a hint of profitability.

Prayank Swaroop, partner at Accel, said that VCs are increasingly expecting AI startups to demonstrate rapid revenue growth. “Even to the pre-seed companies, we say, ‘Hey, you need to show whatever money you have before your next fundraiser. You need to start showing proof that customers are using you.’ Because so many other AI companies exist,” said Swaroop.

AI startups require extensive patient capital from investors as they require extended periods of R&D before their innovations can be brought to market. Arjun Rao, partner at Speciale Invest, also told AIM that it is essential to be patient when investing in AI as these startups are still in the budding stage, and placing the bet on the right founders is paramount. “Founders do not need to worry about the current downturn and keep a long-term mindset,” said Rao.

Meanwhile, most of the startups never see the light of profitability. Even OpenAI, the most invested in and the AI startup with the most users of its product, is still nowhere close to profitability. Maybe, investors need to relook at their investment strategy.

VCs are increasingly not ready to put money in deep-tech startups in India as the need for building use cases is getting more interesting for them, or what some people call OpenAI wrappers and so-called consumer-tech startups, as they require less capital, and possibly quicker revenue.

India’s generative AI scene is on an upswing, but the investors are cautious when it comes to investing in research startups. Though it is rare to find any other initiative being built from scratch, the lack of VCs’ interest in such initiatives also kills R&DNagpur Investment. They just simply don’t want to take the risks.

VCs in India tend to favour proven business models, often pulling out when companies don’t innovate fast enough. VCs withdrew from Byju’s because the company wasn’t “experimenting enough.” The question should be, why did they invest in Byju’s in the first place, despite its shady practices? The answer: capital was cheap, and it was a tested model.

Turns out, even that was a flop.

Despite the pros and cons of the investors, Indian startup founders are also not the ones to not be blamed. India has a surplus of STEM graduates who just want to work for big companies and are too indecisive if they can do a startup in India. Many of them often go to Silicon Valley to build research startups, instead of building in India.

Another sentiment echoed is that most Indian startups are driven by “MBA grads, product managers, and marketers,” rather than engineers. “It’s engineers who need to run companies,” said a user discussing on Reddit, emphasising that successful Western startups are often engineer-led, with a focus on innovation. Current business culture in India is overly focused on replicating successful models rather than developing new ones.

We are a capital-short nation. When capital comes with such a high premium, businesses are understandably hesitant to take risks, especially when labour is relatively cheap. Why would anyone pour limited funds into uncertain R&D when they can invest in low-margin, proven ventures?

One exception to this trend is India’s Unified Payments Interface (UPI), which has been widely hailed as a groundbreaking innovation in digital paymentsSurat Investment. However, UPI succeeded because of government support. Without a similar level of institutional backing, other innovations might struggle to gain traction, which is a valid reason for startups not to do much R&D.

In countries like the US, tax incentives encourage companies to invest in R&D. For example, Amazon benefits from marking even minor improvements under R&D to claim tax benefitsLucknow Stock. In contrast, India’s regulatory framework lacks similar incentives, further discouraging investment in innovation.

This short-term thinking extends to most Indian startups, which prioritise stability over innovation. As another Redditor sums it up, “R&D requires time, the results are uncertain, and it needs good investmentSurat Stock. Indian corporate culture is very much short-term, instant-gratification based.”