Single founders, billion-dollar valuations: AI is minting unicorn startups at birth
But this is less so in Asia, where entrepreneurs seek profitability over valuations: Granite Asia’s Jenny Lee
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[SINGAPORE] Artificial intelligence has fundamentally altered the economics of building a company, to the point where startups can now be effectively born as unicorns, said Jenny Lee, senior managing partner at Granite Asia.
“We are seeing single-founder startups being formed,” she said. “A single founder can get a product up in three to six months, and within less than a year, they are generating revenue.”
In previous technology cycles, Lee noted, building a company required years of runway, teams of 20 to 40 engineers, and three to five years before product-market fit. With AI, that calculus has changed.
The clearest illustration of this shift, she said, is in drug discovery: a field where companies traditionally take 10 to 15 years before generating any revenue.
With AI, that timeline is being dramatically compressed.
Lee cited the case of one company, which has fewer than 100 employees. In just four years, it has generated more than 20 molecules for biologics drug discovery. The company posted more than US$100 million in net profit for 2025 and is targeting US$250 million this year.
“Never before,” she said. “Things are changing faster than we can even imagine.”
Asia’s unicorns are the exception, not the rule
Lee was speaking at a fireside chat presented by HSBC Private Banking and The Business Times at the inaugural Business Conclave, held on Jun 5 at the Dutch Pavilion in Shangri-La Singapore.
“This evening is designed for people who build: founders, business owners and leaders navigating growth, liquidity and what comes next,” said Hammad Hashmi, the market head for Singapore, Malaysia, and Indonesia at HSBC Global Private Banking.
“Entrepreneurs don’t experience wealth in neat categories; their business, liquidity, family plans and investment portfolio are often deeply connected. Bringing together investors and entrepreneurs to exchange perspectives on opportunities, challenges and long-term growth is therefore more important than ever.”
Yet, for all the froth in Western markets – where, as Lee put it, “startups are born unicorns” and single founders command billion-dollar valuations – this phenomenon is far less prevalent in Asia.
Asian entrepreneurs have spent the last five years navigating the Covid-19 pandemic, rising interest rates, a funding drought, and in the case of North Asia, near-total capital withdrawal.
The result is a generation of founders for whom profitability is not a long-term aspiration, but an immediate imperative, said Lee. “They adopt AI and automation with enormous eagerness, because for them it is life and death.”
She added that this pragmatism is reflected in how Asian companies have been pricing their initial public offerings. Many have come to market conservatively, backed by real profits rather than growth multiples, allowing them to be priced at 20 to 30 times earnings.
In contrast, US frontier model companies are growing at rates “never seen before”, but valuations are increasingly difficult to anchor against real revenue.
Asia’s profitability-first founders, by contrast, offer investors a rational entry price and a more grounded working relationship. Lee noted that many are actively seeking partners who can help them navigate supply chain restructuring and operational challenges rather than simply chasing capital.
“Asia still has significant upside to grow, simply because they are fundamentals-based,” she added.
A founder worth backing
The profile of the fundable founder has also shifted considerably, Lee noted.
A decade ago, the template was clear: an operator who had come up through the ranks of a major technology company – the likes of Alibaba, Google, Grab – and was spinning out with deep institutional knowledge and an established network.
Today, Lee said, academics are increasingly worth backing.
The conventional wisdom that academics make poor founders – being too deep in technical expertise and without commercial experience – is being upended by the current wave of AI disruption.
“When a huge technology disruption is coming, it is the technology moat that makes the difference,” she said.
The academics she backs are not those just writing papers. They are researchers who have built industry partnerships, developed proprietary datasets, and are now spinning out companies around small language models, novel AI distribution architectures, or domain-specific applications.
Alongside them, she is also seeing a second cohort: owners of traditional mid-sized businesses who are willing to cannibalise their own models with technology.
The willingness to self-disrupt, she said, is as important a founder trait as any technical credential.
Areas for growth
More broadly, Lee sees three areas for growth over the next three to five years: AI for science; embodied AI, such as robotics; and quantum computing.
On AI for science, she sees potential for AI-native chemistry and biology models to go beyond language to drive genuine research breakthroughs.
On embodied AI, Lee pointed to robotics as a particularly compelling use case in Asia, where automotive manufacturers are pushing the final frontier of factory automation.
Most assembly lines are already 80 to 90 per cent automated, she noted. The remaining gap, where humans are still performing manual testing and assembly tasks, is where she sees the most active research and startup activity.
Looking further out to the five-to-10-year horizon, Lee flagged nuclear fusion and modular energy, and space-based compute as additional areas of interest, with quantum computing potentially arriving sooner than many expect.
“I used to think quantum was 30 years away, but it may be as close as five years,” she said.
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