India short on strong AI startups, says Exfinity’s Bala
Limited innovation and slow enterprise adoption weigh on AI ecosystem
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Bengaluru: India currently lacks a strong pipeline of high-quality artificial intelligence (AI) startups, prompting domestic private equity (PE) and venture capital (VC) firms to increasingly scout for opportunities in the US, according to V. Bala-krishnan, Chairman of Exfinity Venture Partners.
This comes even as several PE and VC firms have raised substantial capital in the past year to invest in AI-led businesses.
“India doesn’t have a strong AI story yet. Fund houses have raised capital but there are not many good startups on the AI side in India. That’s the reason that everyone is trying to figure out something in the US, which does work in India,” Balakrishnan, a former CFO of Infosys, told BizzBuzz. Amid the global AI boom, several marquee and mid-tier investors have launched India-focused funds targeting AI and related technology sectors.
For instance, Accel recently raised a $650 million early-stage fund to back startups across AI, consumer tech, fintech, and manufacturing. The firm has previously invested in companies such as BlackBuck, BlueStone, Cult.fit, Flipkart, Freshworks, Swiggy, Urban Company, and Zetwerk.
Similarly, ChrysCapital raised a record $2.2 billion fund in November 2025, with AI among its key focus areas. The firm has led a $200 million funding round in MoEngage, a customer engagement platform, and also acquired a sig-nificant minority stake in Nash Industries, which operates in IT and AI-linked hardware. Other domestic players are also entering the space. Bajaj Finserv recently an-nounced plans to launch a private equity fund focused on early-stage AI startups.
Industry sources note that while India has a growing number of AI startups, relatively few operate in deep-tech segments. Many lack strong differentiation or proprietary innovation.
At the same time, enterprise adoption of AI has moderated after the initial surge of enthusiasm, with companies factoring in concerns around regulation, data privacy, and security before scaling deployments.
