But that’s not the case in Asia, where entrepreneurs pursue profitability over valuation: Granite Asia’s Jenny Lee
[SINGAPORE] Jenny Lee, senior managing partner at Granite Asia, said artificial intelligence has fundamentally changed the economics of starting a company, to the point where start-ups can effectively be born as unicorns.
“We are seeing more single-founder startups being created,” she said. “A single founder can launch a product in three to six months and generate revenue in less than a year.”
In previous technology cycles, it took years of runway to build a company, a team of 20 to 40 engineers, and three to five years for a product to be market-ready, Lee said. With the advent of AI, that calculation has changed.
Nowhere is this change more evident than in drug discovery, she said. In this space, companies traditionally take 10 to 15 years to generate revenue.
With the advent of AI, that timeline is dramatically shortening.
Lee gave the example of a company with fewer than 100 employees. In just four years, we have generated more than 20 molecules for biologic drug discovery. The company expects to post a net profit of more than USD 100 million in 2025 and is targeting USD 250 million this year.
“This has never happened before,” she said. “Things are changing faster than we can imagine.”
Asian unicorns are the exception, not the rule
Mr. Lee is HSBC Private Banking and business times At the 1st Business Conclave held at the Netherlands Pavilion at Shangri-La Singapore on June 5th.
“Tonight is for founders, executives, leaders and others navigating growth, liquidity and what comes next,” said Hammad Hashmi, market head for Singapore, Malaysia and Indonesia at HSBC Global Private Banking.
“Entrepreneurs do not experience wealth in neat categories; their business, liquidity, family planning, and investment portfolios are often deeply intertwined. Therefore, it is more important than ever to bring investors and entrepreneurs together to exchange perspectives on opportunities, challenges, and long-term growth.”
But while Western markets are frothy, where “startups are natural unicorns” and single founders are valued at billions of dollars, as Lee puts it, this phenomenon is far less common in Asia.
Over the past five years, Asian entrepreneurs have weathered the coronavirus pandemic, rising interest rates, funding shortages and, in the case of North Asia, near-total capital withdrawals.
The result is a generation of founders who see generating revenue as an immediate obligation rather than a long-term aspiration, Lee said. “They’re very enthusiastic about adopting AI and automation because for them it’s a matter of life and death.”
He added that this realism is reflected in the pricing of Asian companies’ initial public offerings. Many companies enter the market conservatively, backed by real profits rather than growth rates, and are priced at 20 to 30 times earnings.
In contrast, U.S. frontier model companies are growing at “unprecedented” rates, but are finding it increasingly difficult to align valuations with real revenues.
In contrast, Asia’s profitability-first founders offer investors reasonable entry prices and more grounded collaborations. Lee pointed out that many are not just chasing capital, but are actively seeking partners who can restructure supply chains and solve operational challenges.
“Asia still has significant upside room for growth simply because it is based on fundamentals,” he added.
Founders worth supporting
The profile of fundable founders has also changed significantly, Lee noted.
Ten years ago, the template was clear. He rose through the ranks from major technology companies such as Alibaba, Google, and Grab and was an independent operator with deep organizational knowledge and established networks.
Today, Lee said, academics are increasingly worth supporting.
The conventional wisdom that academics are poor founders because they have too much technical expertise and no commercial experience is being overturned by the current wave of AI disruption.
“When a major technology disruption occurs, it is the technology moat that makes the difference,” she said.
The scholars she supports are not just academics who write papers. They are researchers who have built industry partnerships, developed proprietary datasets, and are now spinning out companies around small-scale language models, new AI distributed architectures, or domain-specific applications.
In addition to them, she also sees a second group. It’s traditional midsize business owners who are willing to cannibalize their models with technology.
The drive for self-disruption is as important a founder quality as technical qualifications, she said.
Growth field
More broadly, Lee sees three areas of growth over the next three to five years. Embodied AI such as robotics. and quantum computing.
Regarding AI for science, she believes that AI-native chemistry and biology models have the potential to go beyond language and drive real research advances.
When it comes to embodied AI, Lee pointed to robotics as a particularly attractive use case in Asia, where automakers are pushing the final frontier of factory automation.
Most assembly lines are already 80 to 90 percent automated, she noted. The remaining gaps are where humans still do manual testing and assembly work, and that’s where she sees the most active research and startup activity.
Looking ahead another five to 10 years, Lee cited fusion and modular energy and space-based computing as additional areas of interest, and said quantum computing could arrive sooner than many expected.
“I thought quantum was 30 years away, but it might be closer to five years,” she said.
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