Asian stock markets were locked in a tug-of-war in the first half of the year, caught between Middle East tensions and an artificial-intelligence boom that has exposed the gap between AI haves and have-nots.
But cracks are appearing in the AI business, as doubts about the profitability and sustainability of the AI build-out are weighing on tech-heavy indices.
South Korea, Taiwan and Japan – clear beneficiaries of the world’s appetite for components that power AI – were Asia’s top three performing markets during the first half, defying fears that an oil shock caused by the Iran war could derail energy-importing economies.
“Market performance has increasingly become dependent on whether the market sits close to the AI supply chain,” said Charu Chanana, chief investment strategist at Saxo.
Those AI winners now face a reality check as investors begin to demand proof that the huge sums poured into AI will yield real profits and productivity gains.
Although other factors like corporate-governance reforms have also boosted the index, the staggering amount of money investors have poured into AI and tech means the hottest stocks are heavily owned and sensitive to profit-taking.
Excessive concentration among Asia’s AI superstars is causing concerns that investors are putting all their eggs in one basket.
“While fundamentals remain supportive, the intensity of investors’ investments increases the risk of sharp fluctuations,” said Angela Cheng, head of research at CGS International.
Only a handful of stocks in South Korea and Taiwan are making big gains: memory makers Samsung Electronics and SK Hynix, along with contract chip maker Taiwan Semiconductor Manufacturing Co. They are the only Asian companies in the $1 trillion dollar club, all with close ties to AI chip giant Nvidia.
The decline in shares of Samsung and SK Hynix, which together make up about half the total weight of the Kospi index, has prompted several trading halts from authorities to curb volatility.
“A sharp move in any name drags the entire index down with it before the other nearly nine hundred listed companies can speak,” said Xavier Wong at eToro.
AI and chip-related companies have experienced similar ups and downs in Japan.
Tech conglomerates SoftBank—a proxy for AI trading—Advantest and Kioxia, to name a few, have fluctuated sharply as market sentiment swings between enthusiasm over the technology’s long-term promise and pessimism over monetization and sky-high valuations.
Despite increased volatility, all three indices have hit multiple record highs. The value of the Kospi more than doubled in the first half, while the Nikkei jumped 39% and the Taiex jumped 59%.
It remains to be seen whether they can maintain this in the second half.
Loren Tan, director of equity research for Asia at Morningstar, sees the outlook as challenging and perhaps still volatile. Since the tech sector is largely overvalued, investors may look to other sectors with more reasonable returns, such as healthcare, Tan said.
The AI divide is also visible in China’s onshore markets. While AI-enablers like optical module maker Zhongji Innolight and Ioptolink Technology sent the ChiNext index 36% higher, the Shanghai Composite index rose only 3.2%.
Last year, Hong Kong had its best year since 2017. This has not happened yet in 2026. Despite a flurry of listings by tech and AI firms, Hong Kong’s Hang Seng Tech Index has fallen 19% in the first six months.
Drawn by record-setting rallies elsewhere, investors have pulled money out of heavyweight Chinese internet stocks listed in the city. A push factor also came from concerns over AI investment and China’s low consumption.
The Hong Kong market lacks AI infrastructure, analysts at DBS Group Research said in a note. Although valuations are cheap, DBS expects global investors to remain focused on infrastructure and hardware elsewhere.
Despite the disparity, analysts still see plenty of catch-up opportunities in this area, where AI development is still in its infancy.
The first round of AI-led rallies focused on infrastructure names. The next step could be about finding “AI efficiency winners,” Chanana said, which can help companies and markets reduce AI costs or broaden adoption.
Write to Kimberley Kao at kimberley.kao@wsj.com and Sherri Qin at sheerry.qin@wsj.com.
