VCs Rally Behind AI: Unpacking The Hype and Unique India Trends AI entering the pool has also turned out to be a curveball for investors, primarily because AI-first companies behave differently from traditional deep-tech, SaaS, or fintech businesses. Investor expectations of them are also significantly higher.

In the midst of a "new technological paradigm shift,'" according to early-stage investors, Artificial Intelligence (AI) is increasingly being viewed as a generational growth opportunity, but one that demands patience.

As of October 2025, India's generative AI startup space has raised approximately USD 616 million across 64 rounds, according to Tracxn.

AI entering the pool has also turned out to be a curveball for investors, primarily because AI-first companies behave differently from traditional deep-tech, SaaS, or fintech businesses. Investor expectations of them are also significantly higher. Research indicates that this shift is not mere hype: McKinsey estimates that generative AI alone could create between USD 2.6 - 4.4 trillion annual value globally, while an EY study predicts that generative AI could contribute USD 359-438 billion to India's GDP by FY30, and cumulatively up to USD 1.5 trillion between FY24-30.

Despite the promises and potential, VCs are advising caution.

Ujwal Sutaria, Founder and General Partner, TDV Partners, told Entrepreneur India, "AI is relatively new, and it will take time for it to mature. This is a new super cycle, a platform shift that is undergoing. It will become massive, but only over time. This can offer multiple trillion-dollar outcome opportunities as the whole software industry is going to get rewritten over the next decade or two."

The shift has also compelled investors to draw clearer distinctions between AI wrappers and genuine AI companies.

NASSCOM's India Generative AI Startup Landscape report notes that while India now has more than 890 GenAI startups, only a segment of these are meaningfully differentiated. Close to 79 per cent of Indian GenAI firms use proprietary customer data and nearly 45 per cent incorporate synthetic data for fine-tuning, indicating deeper defensibility, while a significant proportion still lack a sustainable compute strategy, a crucial requirement for true AI-first scalability.

An analysis of 914 Indian AI startups showed that AI-era companies attract higher valuations and better offers for capital, though often with lower early-stage per-employee productivity due to heavy spending on R&D, data acquisition, and compute.

This divergence between wrappers and real AI firms is central to VCs' newfound interest.

Firms across the West are already deploying capital at a big scale: NASSCOM data shows USD 54 billion in global GenAI funding in the first half of 2025 alone. Indian, despite showing clear momentum, stands roughly at USD 990 million in cumulative funding for the same period.

The difference, however, is not surprising given India's nascent AI infrastructure and overall ecosystem. As of now, Indian capital firms remain focused on early-stage and applied-AI use cases across sectors such as healthcare, logistics, financial services, and developer tooling, while Western capital increasingly flows to model-building and deep research-led companies. Yet, the structural thesis in India remains strong: a large domestic market, sector-specific data, and lower engineering costs position Indian AI-first startups to scale applications at a rapid pace.

The AI super-cycle may be underway, but investors stay clear-eyed. India may not be building at Silicon Valley's pace, but the funds say the country is entering a decisive phase, one where applied AI companies could scale faster than expected and generate outsized value.