Much has been made of the artificial intelligence race between the United States and China, but it’s South Korea that’s currently making significant headway in its ambitious AI buildout.
In June, President Lee Jae-myung announced plans for at least $880 billion of investments to build out the country’s chip manufacturing and artificial intelligence capabilities over the years ahead. The plans come as part of the country’s Three Mega Projects to develop new chip production hubs domestically, as well as data centers and robotics technology.
While the investment is also focused on boosting the economies of areas outside of Seoul, Lee pointedly claimed that South Korea must outpace regional rivals like China, Taiwan, and Japan, all of whom are investing heavily in chip factories and other advanced technologies as part of a widespread AI boom period.
South Korea has already emerged as an early AI leader thanks to the whirlwind success of its chipmakers SK Hynix and Samsung Electronics, both of which currently make up the lion’s share (around 51 percent) of the nation’s total benchmark KOSPI index market capitalization.
The rise of South Korea’s artificial intelligence chipmakers has been nothing short of emphatic. At the time of writing, SK Hynix’s five-year growth spurt sits at precisely 1,250 percent, while Samsung’s 205 percent rally over the same period is a wild success for a company that’s already long been established as one of the largest in Asia.
But it now appears that plans are firmly underway to ensure that South Korea’s chipmaking strength can help to facilitate a stronger global position when it comes to the AI buildout. But can it really compete with competitors worldwide?
South Korea’s AI prowess is far from a secret. Last month, the Bank of America identified South Korea as the strongest overall AI contender over both the short and long term outside of the United States and China. The brokerage highlighted South Korea’s strength in semiconductor manufacturing alongside its rapidly expanding AI adoption program and supportive government policies as a key catalyst for further growth. This, BoA anticipates, can pave the way from AI deployment into tangible long-term productivity gains.
South Korea also has a hardware monopoly over the global supply of High Bandwidth Memory (HBM) chips, which are essential for training frontier models on Nvidia AI accelerators. Without this hardware, the United States and Chinese software booms wouldn’t be able to function.
However, South Korea has weaknesses as well. It lags behind on both software and large-language models (LLMs), a gap that is widening as the United States and China compete to deliver more powerful and scalable solutions to the market. A national competition to build proprietary LLMs was launched last year, yet the event risked falling into a farce. Multiple finalists relied heavily on foreign open-source code for their models.
But while there are certainly going to be challenges when it comes to competing against rivals in developing powerful AI models, South Korea could find strength in the future through its government-backed plans to create total independence within its own borders. While this could mean a slower buildout, the support of a high-quality infrastructure strategy may help to create a landscape that enhances the capabilities of sovereign models.
One of the biggest challenges that South Korea will need to overcome won’t be in competing directly with China and the United States in their AI buildout, but finding the power needed to deliver its own. The challenge of securing enough stable power, grid capacity, and real estate for massive data center clusters both inside and outside of Seoul is a critical hurdle that the likes of SK Hynix and Samsung won’t be able to solve.
Massive data centers consume far more electricity than more conventional facilities, and industry estimates have shown that a server equipped with eight Nvidia B200 GPUs can require about 20 kilowatts of power, including cooling. A full rack would need around 80 kilowatts, compared with the 3 to 5 kilowatts typically required in traditional data centers.
Given that more than 70 percent of South Korea’s data centers are based in and around Seoul, the prospect of grid overloads, transmission bottlenecks, and power supply stability problems could be highly damaging to the region, according to Park Jong-bae, a professor of electrical and electronics engineering at Konkuk University.
However, the government’s introduction of the Distributed Energy Act, as well as grid impact assessments, has helped to encourage more AI data center development away from the capital, which could help to foster faster AI infrastructure growth.
AI is also forming a symbiotic relationship with its own technological buildout, supporting more efficient construction projects to ensure that nations like South Korea can grow their capabilities faster. This has been especially useful in optimizing supply chains and conducting more efficient risk management. AI can monitor weather conditions, logistics, and geopolitical challenges to ensure that the right construction materials are readily available to support data center buildouts at scale.
South Korea may have a monopoly on high-quality semiconductor manufacturing, but it will be the nation’s $880 billion infrastructure buildout that can support its emergence as a long-term AI powerhouse capable of competing with the likes of the United States and China. However, there are some hurdles to overcome, particularly in managing ambitions to create sovereign AI models without any external reliance, as well as finding the power needed to deliver artificial intelligence infrastructure on a national scale.
Despite this, South Korea has been one of the world’s largest beneficiaries from the AI boom, and it’s certainly an exciting place for investors to track as the runaway success of SK Hynix and Samsung supports a major buildout.
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