Key Takeaways
- • Goldman Sachs estimates prospective Indian AI IPOs over the next 2-5 years could add $50-$100 billion in incremental market capitalization to India's listed AI complex, per its October 19 report.
- • PE investment in Indian AI startups roughly tripled to approximately $5 billion in 2025 from $1.6 billion in 2024, and is on track to surpass that record in 2026, with about $5 billion raised in the first eight to nine months.
- • AI's share of total PE funding for Indian startups quadrupled from roughly 5% in 2024 to around 20% in 2026, according to Goldman Sachs.
- • Goldman's valuation split puts upstream AI enablers at $35 billion, downstream adopters at $18 billion and foundational model developers at $2 billion.
- • Public-market investors have few listed Indian AI companies to invest in, and industry executives expect listings to follow private-market growth over several years.
Summary
India has been largely on the sidelines of the global AI investment boom, with the US, China and Taiwan attracting most attention. Yet private equity investors appear to see opportunity in India's AI ecosystem, even as public-market investors have few sizeable listed companies through which to gain exposure, according to a report published by Mint and syndicated by TradingView.
Goldman Sachs, in its October 19 report, estimated that prospective IPOs over the next two to five years could add $50-$100 billion in incremental market capitalization to India's listed AI complex. The report says PE investment in Indian AI startups tripled in 2025 to approximately $5 billion from $1.6 billion in 2024. Funding has accelerated in 2026, with Indian AI startups raising around $5 billion in the first eight to nine months. The AI share of total PE funding for Indian startups has risen from roughly 5% in 2024 to around 20% in 2026. Goldman cited Stanford University's 2026 AI Index, which ranked India sixth globally for private AI funding in 2025 and fourth for the number of newly funded AI companies.
Goldman estimates upstream AI enablers, including power, semiconductors, data centres, cloud and data management, account for the largest share at $35 billion. Named companies include Greenko Group, Fourth Partner Energy, CtrlS Data Centers, Nxtra Data and Neysa. Downstream adopters are valued at $18 billion and include Gupshup, Kore.ai and NetraDyne. Foundational model developers, including Sarvam AI and Deccan AI, are valued at $2 billion.
Ash Mukherjee of ASK Wealth Advisors attributed limited public-market exposure to a scarcity of listed paper rather than investor underestimation of India's role. Pushkar Jauhari, CEO of private equity and venture capital at Kotak Alternate Asset Managers, said Indian public fund managers have missed the AI trade because India lacks listed companies focused on computing and large language models, and said this would change as private companies scale and list. Ashish Kumar of Fundamentum Partnership said the US AI story is only three to four years old and that India's opportunity extends to enterprise adoption and specialised production. Fundamentum's Frontier Advisors (F2A), anchored by Nandan Nilekani, is raising its maiden fund target by Rs.500 crore to Rs.3,500 crore after stronger-than-expected demand.
For context, PitchBook-NVCA data cited in the article show AI and machine learning deals accounted for 65.4% of US venture deal value in 2025, or $222 billion of $339 billion. Aakash Agrawal of Anand Rathi Investment Banking cautioned there is no automatic link between PE investment and listed-market returns, and that AI gains must show up in revenue and profits. Kumar expects infrastructure companies to potentially list within a couple of years, enterprise AI firms in about three to three-and-a-half years, and vertical and semiconductor businesses in around five years.
Goldman Sachs, in its October 19 report, estimated that prospective IPOs over the next two to five years could add $50-$100 billion in incremental market capitalization to India's listed AI complex. The report says PE investment in Indian AI startups tripled in 2025 to approximately $5 billion from $1.6 billion in 2024. Funding has accelerated in 2026, with Indian AI startups raising around $5 billion in the first eight to nine months. The AI share of total PE funding for Indian startups has risen from roughly 5% in 2024 to around 20% in 2026. Goldman cited Stanford University's 2026 AI Index, which ranked India sixth globally for private AI funding in 2025 and fourth for the number of newly funded AI companies.
Goldman estimates upstream AI enablers, including power, semiconductors, data centres, cloud and data management, account for the largest share at $35 billion. Named companies include Greenko Group, Fourth Partner Energy, CtrlS Data Centers, Nxtra Data and Neysa. Downstream adopters are valued at $18 billion and include Gupshup, Kore.ai and NetraDyne. Foundational model developers, including Sarvam AI and Deccan AI, are valued at $2 billion.
Ash Mukherjee of ASK Wealth Advisors attributed limited public-market exposure to a scarcity of listed paper rather than investor underestimation of India's role. Pushkar Jauhari, CEO of private equity and venture capital at Kotak Alternate Asset Managers, said Indian public fund managers have missed the AI trade because India lacks listed companies focused on computing and large language models, and said this would change as private companies scale and list. Ashish Kumar of Fundamentum Partnership said the US AI story is only three to four years old and that India's opportunity extends to enterprise adoption and specialised production. Fundamentum's Frontier Advisors (F2A), anchored by Nandan Nilekani, is raising its maiden fund target by Rs.500 crore to Rs.3,500 crore after stronger-than-expected demand.
For context, PitchBook-NVCA data cited in the article show AI and machine learning deals accounted for 65.4% of US venture deal value in 2025, or $222 billion of $339 billion. Aakash Agrawal of Anand Rathi Investment Banking cautioned there is no automatic link between PE investment and listed-market returns, and that AI gains must show up in revenue and profits. Kumar expects infrastructure companies to potentially list within a couple of years, enterprise AI firms in about three to three-and-a-half years, and vertical and semiconductor businesses in around five years.
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