Indian AI startups face closer scrutiny over valuations and returns as a sell-off in global tech shares prompts investors to question the cost of the AI boom.
The US Nasdaq Composite has fallen more than 10% from its record high, entering correction territory. Investors are questioning whether huge spending on data centres, chips, and AI infrastructure will generate enough returns, as the cost of developing and adopting AI remains high while returns on investment are low.
Data sourced from Tracxn showed median pre-money valuations of Indian AI startups fell 55% at the Series A stage in April-September 2026 compared with the previous six months, indicating growing pressure on early-stage valuations.
Debraj Banerjee, general partner at Fundamentum Frontier Advisors, said public markets were one valuation input. “Public market multiples do influence exit assumptions over time, and investors across the board are paying closer attention to how today’s valuations translate into realistic outcomes,” he said.
Investors are also examining whether AI companies can turn initial customer interest into sustainable business. “In AI specifically, we look at whether early pilots convert into sustained commercial deployments, how customers renew and expand, and how compute and inference costs affect margins as the business scales,” Banerjee said.
Valuations
Median pre-money valuations at seed fell 8.1% to $5.67 million in April-September 2026, from $6.17 million in October 2025-March 2026. At Series A, they fell 54.6% to $10.8 million from $23.8 million.
However, post-money valuations moved differently. Seed rose 3% to $6.46 million, while Series A increased 18.9% to $27.7 million. Series C pre- and post-money valuations fell 20.3% and 25%.
At Series B, however, median pre-money valuations rose 341% to $1.24 billion and post-money valuations climbed 350% to $900 million.
Banerjee said valuation expectations were not declining uniformly. “Companies with strong teams, differentiated technology and early commercial traction continue to see healthy investor interest and valuations.” In other cases, he said, “conversations between founders and investors have become more grounded, with both sides placing greater weight on fundamentals.”
Tracxn recorded 93 AI startup funding rounds in 2026 so far, against 165 in 2025, a 44% fall. Total funding rose 64% to $1.84 billion from $1.12 billion. The decline in round numbers has been happening through the year.
The scrutiny also varies across the AI value chain. “Foundation models and compute-heavy businesses require substantial long-term capital, so the questions there centre on capital efficiency, differentiation and path to commercialisation,” Banerjee said. On application-layer startups, he said, “revenue visibility can be clearer, but defensibility and depth of integration with customer workflows are equally important.”
Additionally, the overall late-stage funding for Indian tech startups plunged 72% year-on-year to $153 million in October, dragging total monthly funding to a 12-month low of $592.5 million. Early-stage investments bucked the trend, rising 10.8% to $361.6 million, according to Tracxn data.