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Investors have a ‘tough time’ with AI because it’s hard to tell ‘what’s a thin layer on top of what IBM is doing … and what’s truly valuable’

By
Lionel Lim
Lionel Lim
Asia Reporter
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By
Lionel Lim
Lionel Lim
Asia Reporter
Down Arrow Button Icon
August 1, 2024, 7:53 AM ET
Justin Nguyen, general partner at Monk’s Hill Ventures, speaking at Fortune Brainstorm AI Singapore on July 30, 2024.
Justin Nguyen, general partner at Monk’s Hill Ventures, speaking at Fortune Brainstorm AI Singapore on July 30, 2024.Graham Uden for Fortune

Billions of dollars in venture capital money has flooded the AI space over the past year, as firms large and small demand new generative AI services. AI startups raised $12.3 billion between Jan. 1 and Jul. 16, according to TechCrunch citing data from Crunchbase. 

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But the hype isn’t so good for investors, who now need to sort out the good from the bad, and the potentially useful from the completely useless.

“It’s a pretty tough time to be an investor,” said Justin Nguyen, general partner at Monk’s Hill Ventures at the Fortune Brainstorm AI Singapore conference on Wednesday. “It’s very difficult to see what’s the thin layer on top of what IBM is doing, Google is doing, AWS is doing, a thin layer on something that’s pretty commoditized, on these large language models—and what’s truly valuable.”

Value and data

At the end of the day, value will come from the data generated by people using AI applications and how it’s used.

“When anyone can prompt, then what’s proprietary to you?” Nguyen asked. “And how do you go about collecting, amassing, and getting results from that data? A lot of the investing we see are just thin layers on top.”

Ren Yeong Sng, managing director of artificial intelligence strategy and solutions at Temasek, agreed that it wasn’t an “easy time for investors.”

Yet Sng was less focused on data as a source of value. Instead, he suggested that investors value a startup’s ability to continually engage customers. Continued engagement means more data is collected, which in turns builds more value for an AI application. (AI models need large datasets to continuously learn and improve.)

“You need the channel to engage the consumers in order to generate new data that’s fresh in the moat that you want to accrue,” Sng said.

But even if investors find it tough to figure out where to invest in AI, they’re using AI to figure out where to invest. “We ourselves use it to help us identify companies that are interesting,” said Chan Yip Pang, executive director at Vertex Ventures, noting that the VC’s AI is already helping the fund find companies it would have missed in the past. He explained AI can help with sourcing information and picking the right investment target.

And the AI space is likely to expand, as startups emerge to fill a corporate demand for the new technology.

“Sixty percent of CEOs are getting pressure from their investors to do something about AI,” said Juhi McClelland, general manager and managing partner for APAC at IBM Consulting. “When CEOs get pressure, when 60% to 65% of them are being forced to do something, they want to react.”

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About the Author
By Lionel LimAsia Reporter
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Lionel Lim is a Singapore-based reporter covering the Asia-Pacific region.

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