SK Hynix Courts US AI Investors With $29 Billion IPO

South Korean semiconductor maker SK Hynix is preparing to go public in the U.S.

And as Bloomberg News reported Sunday (July 5), the company’s $29 billion listing — set for July 10 and believed to be the largest ever share sale by a foreign firm — is about more than simply raising cash, but about competing for the white hot market for memory chips used in AI computing.

The report noted that SK Hynix has for years struggled to compete with American rival Micron, though entering the world’s largest equity market and its hunger for AI-related investments could help even the odds.

“We are in a time of extreme enthusiasm about chip stocks,” Daniel Morgan, senior portfolio manager at Synovus Trust, which owns shares in Micron, told Bloomberg. “It’s a good time to go and get the U.S. involved in your shares.”

The report also points out that investors are worried about the AI landscape. Companies like Google and Microsoft are turning to debt and equity markets to fund their AI projects. That spending has caused their profits to soar, Bloomberg said, but the dynamic will change if funding dries up.

“Investors run the risk of stepping into something that’s potentially a speculative bubble,” said Ed O’Gorman, CEO at River Wealth Advisors. “You have to be very careful investing in anything that’s up the way these stocks have climbed.”

Last month brought a report that SK Hynix and fellow South Korean tech giant Samsung aim to invest around $518 billion to construct new semiconductor fabrication facilities in their country’s southwestern region. It’s part of a larger national strategy by the government focused on AI and semiconductor projects.

Meanwhile, PYMNTS wrote in May that the idea that “whoever controlled the compute, capital and foundational models would control the future” misses “the harder half: demand.”

At the time, Anthropic announced an small to medium-sized business-focused AI plugin for tools including PayPal, Intuit, Canva, and Docusign, signaling that AI’s next phase could depend less on how much capability technology companies can provide and more on whether ordinary businesses can deliver sustained demand inside everyday work.

“After all, the question facing the market is no longer simply whether frontier models can perform astonishing tasks,” PYMNTS wrote.

“It is whether accountants, nurses, insurance adjusters, teachers, procurement managers, financial analysts and their peers across Main Street can integrate AI into the highly specialized workflows they understand better than any Silicon Valley engineer.”

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