American Companies Are Stocking Up to Get Ahead of Trump’s China Tariffs
Businesses plan to stockpile, raise prices and accelerate shift to manufacturing elsewhere
Businesses plan to stockpile, raise prices and accelerate shift to manufacturing elsewhere
By 9 p.m. on election night, it had become clear to Jason Junod that Donald Trump was returning to the White House. That night, he contacted his skin-care company’s suppliers in China to order a year’s worth of inventory for about $50,000—as much as he could afford to buy and had room to store.
His hope is that the roughly 30,000 body brushes and exfoliating gloves make it to Bare Botanics’ facility in Madison, Wis., before Inauguration Day. He thinks Trump is serious about his campaign promise to impose tariffs of 60% on all Chinese goods.
American businesses are dusting off a playbook they used during Trump’s first term: stocking up on imported goods before tariffs are enacted. They are also considering how to cope with the levies if and when enacted—whether they will be able to raise prices and whether they will need to find alternatives to their Chinese manufacturers.
“The biggest consideration is, do we stay in China?” Junod said.
When Trump began his trade war against China in 2018, U.S. businesses scrambled to front-load imports before tariffs were implemented, according to an International Monetary Fund analysis. As a result, the U.S.’s trade deficit with China—how much imports exceed exports—rose in 2018 before falling in 2019.

Already, exports from China surged last month, which some economists think could have been driven at least in part by front-loading amid uncertainty around election results. Outbound shipments from China rose nearly 13% in October from a year earlier, well above consensus expectations and up sharply from 2.4% growth in September.
Chinese exports growth should remain strong through the next few months because of front-loading, Wall Street economists said.
China remains the world’s top exporter of goods and the U.S. its top buyer. American companies bought roughly $430 billion of Chinese goods last year, with computer and electronic products making up the biggest chunk.
Wan Junhui, who works in marketing for an electronics manufacturer in Guangdong province, said his company has observed an increase in inquiries and “noticeable unease” from its U.S. clients recently. He said that tariffs so far haven’t affected sales significantly, but that buyers end up absorbing the levies and sometimes raising prices for their end customers.
“We’ll do our best to focus on reducing costs to help ease the situation and make it through this harsh winter,” he said.
Though China’s share of U.S. imports has declined to roughly 14% in 2023, from 22% in 2017, rising tariffs between the U.S. and China have done little to curb the overall U.S. trade deficit in global trade or China’s overall trade surplus.

The persistent trade imbalance is driven by strong demand from American consumers and weakening domestic demand in China, according to the IMF. U.S. firms have boosted their share of imports from places such as Vietnam, while China has increased exports to regions including Southeast Asia.
Tariffs aren’t paid by exporters, but rather by businesses that import products. Economists say those businesses usually pass on the bulk of the cost to consumers by raising prices.
Some economists doubt the U.S. will succeed in raising tariffs to 60% across the board on Chinese products. Economists at Goldman Sachs predict additional duties on China could average out to a 20 percentage-point increase in the effective tariff rate.
In addition to duties on Chinese goods, Trump proposed tariffs of 10% to 20% on imports from all countries.
That would be the worst-case scenario for Leah Dark-Fleury, co-founder of Stone Fleury, a natural-stone and porcelain wholesaler in San Francisco. She has been buying natural stone from the same supplier in China for two decades and imports most of her other materials from Europe.
When Trump imposed a tariff on Chinese natural stone during his first term, Dark-Fleury continued buying from China as usual. The company raised prices to compensate, but tried to not charge the full increase to stay competitive.
This week, she asked her supplier in China about the possibility of ordering about two shipping containers’ worth of natural stone under a payment plan to try to get ahead of tariffs. That could cost up to around $100,000 and last her between a few months and a year, depending on customer demand. In the longer run, she expects to raise prices on materials from China and shift some sourcing to Vietnam.
“I wish that I could buy enough to get us through the four years,” she said.
Toni Norton , owner of Fine Fit Sisters in Charlotte, N.C., sources body oil from China that is popular with customers in the summertime. She normally wouldn’t be stocking up until the new year, but is trying to order about 20,000 units before the end of the year.
If tariffs on Chinese products indeed reach 60%, Norton said she might have to stop selling body oil and focus more on her fitness-coaching services. She said she doesn’t think she has much room to raise prices on the body oil, which she mostly advertises on TikTok and sells for about $13, because “people like cheap things.”
Front-loading imports “is a short-term solution,” said Chris Tang , a professor of supply-chain management at the University of California, Los Angeles. Businesses are likely to need additional strategies in a world with persistently higher and broader tariffs.
Companies have already been moving manufacturing from China to places such as Southeast Asia and Latin America, a trend that is expected to continue—if buyers are able to find a suitable alternative to Chinese production.
A 2024 survey by Bain & Company found that 69% of chief executives and chief operating officers plan to reduce their company’s dependence on China, up from 55% in 2022.
Ryan Bursky , CEO of Lucidity Lights, a maker of lighting products in Boston, said the expectation of new tariffs is only accelerating a process under way at his company. Lucidity Lights made a strategic decision last year to begin sourcing outside of China, where it had previously done all of its production, in part because of the first phase of the trade war.
The company is on track to do about 15% of production in Cambodia this year, with plans to move about half of production out of China next year. He believes it is a better use of resources to invest in supply-chain diversification, rather than stockpiling.
Bursky said it has taken some time to find the right suppliers in Cambodia, which is still growing its manufacturing capacity and speed. But he thinks that the products made in Cambodia are better quality and that there is more attention to detail.
Joe Jurken , the founder and managing director of the ABC Group in Milwaukee, which helps U.S. businesses manage supply chains in Asia, expects China to still dominate manufacturing somewhat, even as his clients have beefed up sourcing from countries such as Vietnam, India and Cambodia.
China has developed infrastructure, communication and transaction channels that make doing business easy for Western companies, while those systems are still being developed in other countries, he said. Plus, it is hard for manufacturers in other countries to beat Chinese suppliers’ low prices.
“China will never be replaced,” Jurken said. “Other markets are an alternative.”
Junod, who started his skin-care business in 2020, has considered looking for manufacturers in Southeast Asia, but believes it would be difficult to replicate the low cost and high quality he has come to rely on from his Chinese suppliers.
“It feels like we’re being punished because there isn’t really anywhere else for us to turn domestically,” he said of Trump’s proposed tariffs. “We have no choice, really, but to pay them.”
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Technology and semiconductor shares fell sharply as investors questioned the debt financing the AI infrastructure boom and confronted higher rates and Chinese competition.
Technology and semiconductor shares fell sharply as investors questioned the debt financing the AI infrastructure boom and confronted higher rates and Chinese competition.
A sharp technology sell-off has exposed a new anxiety on global markets: whether the enormous borrowing behind the artificial-intelligence infrastructure boom can generate sufficient returns as interest rates rise and Chinese competition intensifies.
The artificial-intelligence investment boom has powered technology shares, semiconductor manufacturers and data-centre operators to extraordinary heights. Last week, investors were given a reminder that much of this expansion is being built with borrowed money.
The technology-heavy Nasdaq Composite fell 4.5 per cent over the week ended October 16, its weakest performance since late June. Semiconductor shares suffered an even deeper correction, with the Philadelphia Semiconductor Index losing about 11.4 per cent.
The selling spread quickly through global markets. Micron Technology fell 14.6 per cent over the week, while South Korea’s Samsung Electronics and SK Hynix dropped approximately 18 per cent and 24 per cent respectively.
This was more than a routine bout of profit-taking. Investors were reassessing three interconnected risks: higher interest rates, the rapidly expanding debt burden attached to AI infrastructure and the prospect of stronger competition from Chinese memory-chip manufacturers.
Artificial intelligence requires a physical infrastructure network of enormous scale. Data centres must be built, advanced processors purchased, power supplies secured and cooling systems installed before customers begin generating meaningful revenue from them.
Technology companies are increasingly supplementing their own cash with corporate bonds, syndicated loans, equipment leases, private credit and project-level financing.
JPMorgan describes the emerging funding model as a combination of conventional corporate borrowing and project finance tied to individual data-centre assets. In Australia, the Reserve Bank estimates that syndicated loans accounted for approximately three-quarters of data-centre financing during 2025 and 2026 to date.
The numbers are becoming large enough to affect broader credit markets. The Federal Reserve Bank of Dallas has cited Wall Street estimates suggesting AI-related investment-grade bond issuance could approach US$300 billion in 2026 alone.
That borrowing is not automatically problematic. Debt can be an efficient way to finance long-lived infrastructure when future revenue is sufficiently predictable. The concern is that AI technology, customer demand and computing economics are changing much faster than the repayment schedules attached to the assets.
A data centre financed today may carry debt for years. Investors must therefore make assumptions about future utilisation rates, electricity prices, chip performance, customer concentration and the amount businesses will ultimately pay for AI computing.
When interest rates rise, those assumptions become less forgiving.
September’s US inflation data intensified the pressure. Consumer prices increased 3.7 per cent over the year, ahead of market expectations and up from 3.4 per cent in August.
The hotter reading reduced confidence that interest rates would fall quickly and pushed bond yields higher. That matters particularly for companies whose valuations depend on profits expected well into the future, as well as highly leveraged infrastructure operators that may need to refinance.
CoreWeave has emerged as a closely watched test case. The specialist cloud-computing company has accumulated substantial debt and lease obligations to build AI capacity, while relying on a concentrated group of large technology customers.
Its shares fell sharply during the sell-off, while the cost of insuring its debt against default climbed. CoreWeave has argued that its contracted backlog more than covers its obligations and that financial markets do not always understand its business model. Nevertheless, its securities have become a proxy for investor confidence in debt-funded AI infrastructure.
Oracle, another major investor in AI computing capacity, fell 8.8 per cent in Friday trading, while CoreWeave dropped 15.5 per cent.
The question is shifting from how much AI infrastructure can be built to how profitably it can be operated.
Interest rates were not the only catalyst. Reports of advances by Chinese memory-chip producer ChangXin Memory Technologies raised concerns that lower-cost Chinese products could increase competition across the global semiconductor industry.
Memory chips are essential to AI systems, but the industry is historically cyclical. Periods of tight supply and high pricing can encourage rapid investment, eventually producing oversupply and falling margins.
The prospect of a well-funded Chinese competitor expanding its technological capabilities unsettled investors in Samsung, SK Hynix and Micron. It also demonstrated that AI-related demand does not insulate chipmakers from conventional competitive pressures.
That combination—slower rate cuts, more expensive financing and potentially cheaper supply—challenged the assumption that every company exposed to AI would enjoy continually expanding margins.
The sell-off does not establish that the AI boom is ending. Demand for computing power remains strong, the largest technology companies continue to generate formidable cash flows and many infrastructure projects are backed by long-term customer contracts.
What has changed is the market’s willingness to overlook the price and financing structure of that growth.
The most resilient companies are likely to be those able to fund investment from operating cash flow, secure long-duration customers and demonstrate that new capacity will earn returns comfortably above its financing costs.
More speculative operators may face greater scrutiny, particularly where debt is expensive, customers are concentrated or expected revenue depends on demand that has not yet materialised.
For Australian investors, the lesson extends beyond US technology shares. Local data-centre operators, infrastructure funds, electricity suppliers and property groups are increasingly exposed to the same investment cycle.
Artificial intelligence may remain one of the defining growth themes of the decade. But last week’s correction showed that enthusiasm for the technology does not eliminate financial discipline.
The next stage of the AI boom will be judged not only by computing power, model performance or demand for chips, but by something more traditional: whether the assets being financed can generate enough cash to repay the money borrowed to build them.
Nasdaq Composite: Down 4.5 per cent for the week ended October 16, 2026
Philadelphia Semiconductor Index: Down approximately 11.4 per cent
Micron Technology: Down approximately 14.6 per cent
Samsung Electronics: Down approximately 18 per cent
SK Hynix: Down approximately 24 per cent
US September inflation: 3.7 per cent annually
Estimated 2026 AI-related investment-grade issuance: Approximately US$300 billion
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