Chinese artificial intelligence supply-chain companies are expected to sustain their Hong Kong listing plans despite growing concerns about stretched valuations and volatility in global AI infrastructure stocks, as strong mainland investor demand and international capital provide support for the market, according to Citi.
Simon Yuan, Citi’s head of China investment banking and Asia-Pacific head of financial institutions, said recent valuation pullbacks among data-center companies, particularly in the United States, were unlikely to derail the pipeline of Chinese AI-related listings in Hong Kong.
The market’s resilience is supported by a relatively balanced mix of domestic Chinese and international investors, Yuan said on the sidelines of the International Monetary Fund meetings in Bangkok. Increasing capital flows from mainland China into Hong Kong equities have also become an important source of demand, helping companies seeking to raise funds access a broader pool of investors.
Register for the next Tekedia Mini-MBA.
Register for Tekedia AI in Business Masterclass.
Join Tekedia Capital Syndicate and co-invest in great global startups.
However, Yuan cautioned that Hong Kong would not be insulated from a reversal in global AI investment sentiment.
“If the whole AI cycle turns in the US — and we have seen some volatility in the last few weeks — you will see an impact everywhere, Hong Kong included,” he said.
His assessment underpins the contrast between the continued demand for AI infrastructure and the financial risks emerging as investors reassess the valuations and funding requirements of companies supporting the boom. Chinese hardware suppliers have benefited from rising demand for computing infrastructure, but their listing prospects will ultimately remain tied to investor confidence in the durability of AI spending.
The outlook also points to a potential change in the composition of Hong Kong’s equity capital markets. While hardware manufacturers and suppliers have been major beneficiaries of the infrastructure build-out, Yuan expects attention to shift next year towards Chinese AI model developers and application companies. Those businesses, however, will face a more demanding test: demonstrating that rapid technological progress can translate into sustainable revenue and profitability.
Hong Kong’s role as a financing center for Chinese technology companies has strengthened amid renewed demand for AI-related investment. Yuan said the market benefits from a roughly even split between mainland Chinese and international demand for Chinese companies seeking to list, giving issuers access to investors with different sources of capital and investment priorities.
Southbound investment, through which mainland investors buy Hong Kong-listed shares, has become an important part of that support. The additional liquidity can help absorb new share offerings and broaden the investor base for companies seeking capital to expand production, develop technology or strengthen their international operations.
That support is necessary as global investors become more selective about AI-related businesses. The recent pullbacks in data-center valuations in the United States have raised questions about how much of the anticipated growth in AI infrastructure has already been incorporated into share prices and whether future earnings will justify the scale of investment.
For Chinese hardware companies, the immediate challenge is to distinguish strong operating performance from the risks embedded in market valuations. Yuan said suppliers have benefited from both higher sales volumes and rising unit prices as demand for AI infrastructure has expanded.
That combination is expected to strengthen revenue growth and improve earnings potential, particularly for companies supplying components and equipment required to build computing capacity. However, the sustainability of those gains depends on continued investment by major technology companies and data-center operators.
If spending slows, hardware suppliers could face weaker orders, greater pricing pressure or a deterioration in investor expectations. A sharp reversal in the global AI cycle could therefore affect Chinese companies even where their immediate operating performance remains strong.
Yuan’s warning also suggests that Hong Kong’s domestic liquidity advantage should not be mistaken for insulation from global market conditions. Mainland investors may help sustain demand for new listings, but their willingness to absorb offerings will still be influenced by valuations, expected returns and broader sentiment towards technology stocks.
Chinese Hardware Firms Expand Overseas As Market Focus Evolves
Chinese AI hardware suppliers have also been adjusting their manufacturing strategies to serve international customers and manage geopolitical risks. Yuan said many companies had proactively established production footprints outside mainland China, helping them meet the needs of global clients while reducing exposure to trade and political tensions.
Overseas manufacturing can provide greater flexibility in supplying multinational customers, particularly when trade restrictions or geopolitical friction complicate cross-border business. It may also help companies diversify production and maintain access to markets where customers are seeking alternatives to concentrated supply chains.
The approach is important for Chinese technology businesses whose growth depends on international demand. Although their manufacturing capabilities have helped them capture opportunities from the AI infrastructure boom, their long-term prospects also depend on their ability to navigate shifting trade policies and maintain relationships with global customers.
The next stage of Hong Kong’s AI listing cycle could bring a different set of challenges. Yuan expects the focus in equity capital markets next year to move beyond hardware suppliers towards Chinese AI model developers and application companies.
Such a transition would mark a shift from businesses supplying the physical infrastructure needed to run AI systems towards those developing models and commercial products that use that infrastructure. It could broaden the range of AI-related investment opportunities available in Hong Kong, but it would also place greater emphasis on the commercial performance of software and AI businesses.
For model developers and application companies, technological capability alone may not be sufficient to attract investors at demanding valuations. Companies will need to show that customers are willing to pay for their products, that revenue can expand at a strong pace and that their business models can eventually generate consistent profits.
“But these companies need to have a proven business model. They need to show very strong growth and profitability,” Yuan said.
The emphasis on profitability is significant because many AI developers face substantial computing costs, ongoing research spending, and pressure to scale their products quickly. Even where demand is growing, companies must demonstrate that revenue can cover those expenses without requiring continual capital injections.
Against that backdrop, investors are likely to scrutinize customer retention, recurring revenue, operating margins and the cost of providing AI services more closely as the market expands beyond hardware. Companies that can demonstrate repeatable commercial demand may be better positioned to attract capital, while those relying primarily on growth expectations could find fundraising more difficult if sentiment deteriorates.
The strength of Hong Kong’s listing market is reflected in its fundraising figures. A total of 118 companies went public in the city during the first nine months of the year, raising HK$388 billion, equivalent to approximately $49.4 billion. Proceeds increased 106% year-on-year, driven in part by Chinese technology companies seeking funding.
The surge in capital raising highlights Hong Kong’s continued importance as a destination for Chinese companies seeking access to public equity markets. It also provides a potential financing channel for businesses requiring substantial investment to expand manufacturing capacity, develop AI models and commercialize new applications.
However, strong aggregate fundraising does not guarantee that every company entering the market will receive favorable valuations or maintain investor support after listing. As the AI investment cycle matures, investors may increasingly distinguish between companies with established revenue streams and those whose valuations depend on expectations of future growth.