Goldman Sachs has urged clients to increase exposure to China’s artificial intelligence supply chain, estimating the country’s AI-related value chain at about $4 trillion, even as global mutual funds remain heavily underweight in Chinese technology assets. The recommendation comes as governments, chipmakers, cloud companies and large platforms race to secure computing power, memory supply and AI applications, while traders weigh whether the next phase of the AI trade will broaden beyond U.S. megacap technology shares.
The bank’s view centers on a broad basket of Chinese companies linked to power generation, semiconductors, data-center infrastructure and AI applications. Goldman said global mutual funds allocate only about 1.2% of their technology exposure to China, a level that suggests room for portfolio rebalancing if sentiment toward the country’s technology sector improves.
The call also lands at a time of sharp divergence across global AI trades. In China, the focus is shifting toward domestic hardware, memory chips, cloud infrastructure and policy-backed technology spending. In India, traders are using the Nifty IT Index as a way to express concern that generative AI could reduce demand for parts of the country’s software outsourcing model. In the United States, semiconductor listings, tokenization companies and corporate Bitcoin holdings are all being reassessed against a backdrop of tighter regulation, changing capital needs and uneven demand for risk assets.
The crypto sector is facing its own reset. New digital asset rules in Europe have pushed offshore stablecoin activity away from regulated platforms, while approved digital dollar products have expanded rapidly. At the same time, companies holding Bitcoin on their balance sheets are beginning to treat the asset less like a static reserve and more like a flexible source of corporate liquidity.
China’s AI chain draws renewed attention
Goldman Sachs’ China AI strategy basket reflects a market view that the country’s AI opportunity is not limited to consumer-facing chatbots or software applications. The bank’s recommended exposure spans across the underlying layers needed to support large-scale AI development, including electricity generation, semiconductor production, data-center construction, cloud infrastructure and enterprise AI products.
That structure reflects the scale of the buildout now under way. AI systems require large volumes of power, high-performance chips, memory, cooling systems, networking equipment and software services. In China, state policy has reinforced this trend by encouraging domestic substitution in strategic technologies and by supporting data-center and computing infrastructure projects.
The bank estimated China’s AI value chain at roughly $4 trillion. Despite that scale, foreign fund exposure remains low after years of regulatory uncertainty, geopolitical pressure, property-sector weakness and concerns over China’s economic recovery. The 1.2% allocation figure cited by Goldman suggests many global portfolios still treat Chinese technology shares as a marginal holding rather than a core part of the global AI trade.
For traders, the key question is whether China’s AI sector can show durable earnings growth rather than only policy momentum. Goldman’s analysts pointed to several risks that could affect the trade, including whether data-center spending remains strong, whether memory capacity expands in a disciplined way, and whether Chinese technology companies can turn domestic development into export revenue.
The distinction matters because AI infrastructure spending can move in cycles. A rapid buildout often lifts equipment makers and component suppliers first, but later phases depend on whether applications generate enough revenue to justify continued capital expenditure. If demand falls short, companies exposed to servers, power systems and memory chips can face margin pressure and excess capacity.
Indian IT shares face pressure from AI fears
While China’s AI trade is being framed as a growth opportunity, India’s technology outsourcing sector is being viewed by some traders as a potential casualty of the same trend. The Nifty IT Index has become a proxy for concerns that AI tools may replace or reduce demand for certain forms of white-collar labor, especially in coding, testing, business-process support and outsourced engineering services.
India’s large software exporters built their global model around skilled labor, offshore delivery centers and long-term contracts with overseas corporate clients, particularly in the United States. That model is now being tested by two forces at once: slower discretionary technology spending by clients and the adoption of generative AI tools that can automate some of the work once performed by large staffing teams.
Reduced U.S. visa issuances have also added pressure. Indian IT firms have historically used overseas placements for client management, implementation and engineering support. A tighter visa environment can raise delivery costs and complicate project staffing, while AI adoption may weaken the need for large headcounts in certain service lines.
The impact is unlikely to be uniform. Higher-end consulting, cybersecurity, cloud migration and AI integration services may remain in demand, while lower-margin staffing-heavy contracts could face deflation. But for equity markets, the concern is straightforward: if clients can do more work with fewer outsourced employees, revenue growth and billing rates for traditional IT service providers may come under strain.
U.S. account initiative adds another market link
In the United States, the Treasury launched the “Trump Accounts” initiative on July 4, allowing users to make donations and view account balances through an official platform. The program has attracted attention because early stock donors, including companies such as SpaceX, may gain indirect exposure benefits through index-linked structures and service providers connected to the system.
The accounts are expected to create links with the S&P 500 and with financial infrastructure firms, including custody and brokerage service providers such as BNY Mellon and Robinhood. Those connections could give the program broader market relevance beyond the initial political and policy debate around its creation.
The market effect will depend on the size of contributions, the mechanics of asset allocation and the number of users who participate. If account flows are directed into broad equity exposure, they could provide incremental demand for index-linked products. If the platform becomes a major retail savings channel, service providers involved in custody, trading or account administration could benefit from scale.
Still, traders are likely to focus less on the announcement itself and more on implementation. Account infrastructure, fee structures, eligible assets, contribution rules and political durability will determine whether the program becomes a meaningful financial channel or remains a limited initiative.
SK Hynix listing underscores AI chip appetite
Demand for AI hardware remains strong despite recent volatility in semiconductor stocks. SK Hynix’s American Depositary Receipt sale drew more than seven times the expected demand, positioning it among the largest foreign listings in U.S. history. The offering highlights continued appetite for companies tied to high-bandwidth memory and advanced chips used in AI servers.
SK Hynix has been one of the major beneficiaries of the AI infrastructure boom because of its role in memory chips used alongside advanced graphics processors. High-bandwidth memory has become a critical component for training and running large AI models, and supply constraints have supported pricing across parts of the memory market.
The strong reception for the ADR sale came even as the broader semiconductor market has been undergoing a correction. Chip stocks rallied heavily during the first phase of the AI boom, leaving valuations sensitive to any sign of slower spending by cloud giants or weaker demand from data-center operators.
Upcoming quarterly reports from major technology companies are expected to be important for the sector’s next move. Traders will be looking for guidance on capital expenditure, server demand, AI chip orders and the pace of data-center expansion. Any slowdown in planned spending could pressure suppliers, while confirmation of sustained AI infrastructure budgets would support the broader hardware chain.
Tokenization listing hit by patent dispute
The risks in newer digital-asset-linked equities were highlighted by the sharp drop in Securitize’s market value after its public listing. The tokenization firm lost more than 40% of its market value within a week after competitor tZERO alleged patent infringement involving Securitize’s DS Protocol and Vault Registrar products.
Securitize had entered public markets through a SPAC merger, a route that has often produced high volatility after listing. SPAC transactions can bring companies to market quickly, but they also expose newly listed firms to rapid shareholder turnover as short-term capital exits and longer-term equity holders reassess valuation, legal risk and execution plans.
The patent claim added another layer of uncertainty. Tokenization platforms depend heavily on software architecture, compliance systems, recordkeeping tools and transfer mechanisms. If core technology becomes subject to legal challenge, traders may demand a higher risk premium until the dispute is resolved or its financial impact becomes clearer.
The episode also shows that blockchain-related market infrastructure is not immune to traditional intellectual-property risks. While tokenization is often marketed as a modernization of securities issuance, settlement and ownership records, the companies involved must still defend their technology, navigate licensing questions and prove that their systems can operate within regulated markets.
CXMT advances in China’s memory sector
China’s semiconductor ambitions are also moving forward through ChangXin Memory Technologies, known as CXMT. The company has advanced toward partnerships with major technology brands, including Apple and Google, while expanding domestic supply relationships with large Chinese technology groups.
CXMT signed a 20 billion yuan DRAM supply agreement with Tencent and lists domestic clients such as Alibaba Cloud and ByteDance in its filings. These relationships point to growing demand for local memory supply as Chinese firms seek alternatives to foreign components amid geopolitical uncertainty and export controls.
Apple is reportedly seeking U.S. government approval to include CXMT in its supply chain for Mac and iPad memory components. If approved, that would represent a significant step for the Chinese memory maker, potentially giving it access to one of the world’s most demanding consumer electronics supply chains.
The company’s recent profit growth has been supported by high DRAM prices. However, much of that earnings strength appears tied to cyclical pricing conditions rather than a proven long-term structural advantage. Memory markets are historically volatile, with profits rising sharply during shortages and falling when capacity expands too quickly.
For China, CXMT’s importance extends beyond short-term profits. Domestic DRAM production is a strategic objective because memory chips are essential for servers, smartphones, computers and AI infrastructure. Broader adoption by major customers would strengthen China’s technology supply chain, but the company still faces challenges in process technology, yield, scale and export restrictions.
Europe’s crypto rules reshape stablecoin market
The European Union’s Markets in Crypto-Assets regulation, known as MiCA, has begun to reshape the region’s digital money market. Tether has withdrawn services from the region, while Circle has obtained a French electronic money institution license that allows it to operate under the new framework.
The change formally brings Circle’s USDC and EURC stablecoins into the EU’s compliance structure. For traders, the key shift is that stablecoins in the region are no longer competing only on liquidity and brand recognition. Regulatory authorization has become central to whether a product can remain available on compliant platforms.
Strict digital money rules have caused offshore cash-like instruments to disappear quickly from some regional trading venues. Approved assets have moved into the gap, reaching an estimated market size of about $73 billion by the start of July. Financial reports also show that compliant digital dollar products cleared nearly $1.79 trillion in payments last month.
The legal window closed on July 1, leaving many older digital asset businesses without the required permits. Some estimates suggest about 83% of legacy digital asset firms were not properly authorized when the rule change took effect. That creates operational risks for users of non-compliant platforms, including account restrictions, delistings and loss of access to certain products.
The transition marks a significant phase in the institutionalization of stablecoins. In earlier years, traders often prioritized liquidity, speed and platform availability. Under MiCA, legal status, reserve structure, redemption rights and issuer licensing are becoming equally important. This may favor firms that can absorb compliance costs and maintain transparent reserve practices, while pushing offshore or lightly regulated issuers out of mainstream European channels.
MicroStrategy’s Bitcoin approach signals a shift
MicroStrategy’s Bitcoin strategy is also drawing renewed attention because of how the company categorizes sales and reserve activity. The company has sold Bitcoin beyond its previously declared $1.25 billion ceiling by separating transactions into “building” and “replenishing” reserve categories, according to the figures described in market materials.
This accounting framework allows the company to treat its capital structure as a set of connected components: common shares, preferred shares, reserves and Bitcoin holdings. Rather than presenting Bitcoin only as an asset to accumulate, the structure makes it part of a balance-management system designed to support financing needs and preferred stock obligations.
The approach represents a meaningful shift in how corporate Bitcoin holdings may be interpreted. A pure buy-and-hold model implies that coins are largely removed from liquid supply. A balance-management model implies that coins may return to the market when corporate finance needs require liquidity.
Market commentary cited the sale of 3,588 coins and said the company’s total stash fell to 843,775 units to cover internal stock payouts. Under that style of management, Bitcoin becomes an adjustable balance sheet tool rather than an untouched reserve. The practical consequence is that traders may need to watch corporate treasury policies as closely as wallet balances.
Large public-company holders can influence market psychology because their activity is visible and often tied to financing cycles. If sales become more routine, especially around key price levels or payout dates, they could add supply at moments when the market is already sensitive to liquidity conditions. Some traders have focused on the $64,000 area as a level where selling pressure from corporate sources could become relevant, though actual market impact would depend on order execution, volume and broader demand.
The broader implication is that Bitcoin scarcity narratives are becoming more complex. Fixed protocol supply remains unchanged, but liquid market supply can still rise when large holders sell for corporate reasons. Treasury strategy, debt obligations, preferred share programs and reserve classifications can all affect how much Bitcoin is available to the market at any given time.
Hardware supply looks steadier than speculative platforms
Across these developments, a divide is emerging between tangible AI infrastructure and more speculative digital-asset-linked business models. Hardware suppliers tied to state-backed technology plans, memory demand and confirmed corporate supply agreements are attracting renewed attention. Tokenization firms and lightly regulated digital money platforms, by contrast, are facing legal, regulatory and post-listing volatility.
That does not mean hardware trades are risk-free. Semiconductor demand is cyclical, AI capital spending can slow, and memory markets can turn quickly when supply expands. Chinese technology companies also remain exposed to export controls, geopolitical restrictions and domestic policy shifts.
But the market appears to be placing greater weight on verifiable supply contracts, patent positions, customer relationships and regulatory authorization. The sharp moves in Securitize, the MiCA-driven stablecoin shakeout, the strong demand for SK Hynix’s ADR sale and Goldman’s China AI recommendation all point to the same conclusion: traders are separating durable infrastructure from products that depend heavily on sentiment, legal ambiguity or yield-driven flows.
The next phase of the AI and digital asset trade is likely to be shaped by execution rather than slogans. In China, that means proving that AI spending can produce revenue across applications and infrastructure. In India, it means showing that IT services can adapt to automation rather than be displaced by it. In Europe, it means operating stablecoins inside clear legal boundaries. In the United States, it means watching whether corporate Bitcoin holders behave like long-term accumulators or active treasury managers.
For global markets, the message is increasingly practical. Capital is still moving toward AI and digital infrastructure, but it is becoming more selective. Companies with real demand, regulatory clearance, defensible technology and transparent balance sheets are gaining an advantage, while those exposed to legal disputes, unclear compliance status or fragile narratives are being repriced quickly.
Explore AI-driven trading strategies aligned with China’s AI boom using our AI copy trading tools for smarter market exposure.
Disclaimer: The content on this page is provided for general informational purposes only and does not represent the views or financial advice of Toobit. We make no guarantees regarding the accuracy or completeness of this information and shall not be held liable for any errors, omissions, or outcomes resulting from its use. Investing in digital assets involves risk; users should independently evaluate their financial situation and the risks involved. For further details, please consult our Terms of Service and Risk Disclosure.
