Upstream Nvidia and TSMC are making huge profits, while downstream players face high debt and low profits—the current situation of the AI industry chain.

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The boom in artificial intelligence (AI) is creating a sharply divided industry landscape. Upstream manufacturers of chips and servers are enjoying substantial profits, while many downstream cloud service providers and application developers are mired in high costs and low profits, with rising debt levels sounding an alarm for the sector.

The latest example comes from software giant Oracle. According to The Information, the company’s rapidly growing AI cloud rental business is eating into its generous profits. Financial reports show that for the three months ending in August, Oracle’s gross profit margin for renting Nvidia chip servers was only 14%, far below the company’s overall gross margin of about 70%. This news caused Oracle’s stock price to plummet by as much as 5% and dragged down the broader market.

Oracle’s predicament is not unique. Due to the high prices of Nvidia chips, all cloud service companies offering AI computing rentals face profit pressure. Meanwhile, both Goldman Sachs and JPMorgan issued warnings this week, noting that the debt levels of tech companies funding the AI boom have crossed an important threshold, and these companies are increasingly turning to credit markets to support high development costs.

This series of developments clearly shows that although the AI narrative remains engaging, the path to commercialization and profitability is proving longer and bumpier than expected for most participants. For investors and enterprises, the core question now is: Are the returns from AI services truly worth their significant costs?

A Feast for Hardware Giants

In the current AI race, the biggest winners are the companies providing infrastructure for AI. From chip manufacturer Nvidia and chip foundry TSMC to server supplier Dell, these upstream enterprises are turning huge market demand into real profits.

Dell’s performance provides strong evidence. The company has doubled its annual revenue growth forecast to between 7%-9%, and doubled its profit growth forecast to at least 15%. Dell has clearly stated that this is due to strong demand in the market for servers equipped with AI chips. These hardware giants hold the “tickets” to the AI industry and are capturing most of the value at this stage.

The “Revenue Without Profit” Dilemma of Cloud Providers

In sharp contrast to the huge profits upstream, cloud service providers in the midstream of the industry chain are facing the embarrassment of “growing revenue without growing profits.” While they have achieved rapid revenue growth by providing AI computing power, their profitability has been seriously squeezed.

Oracle’s case is quite representative. Although the company expects its AI cloud rental revenue to grow substantially by 2030 and possibly become a major revenue source, this will likely come at the expense of overall profit margins. The root of the problem lies in the high cost of Nvidia chips, which leaves cloud providers with meager profits from their computing power rental businesses. For an industry accustomed to high profit margins, the profitability brought by AI business is far from expected.

High Costs and the Profitability Challenge

For AI model developers and application vendors further downstream, the profit outlook is equally uncertain. Currently, there is almost no evidence that selling AI applications to businesses or individuals is a profitable business.

The development and operating costs of AI models are a heavy burden for all AI applications. For example, the profit margin for applications such as programming assistants isn’t high. Although these costs have declined over time, the challenges of commercialization remain significant. Many large listed companies are secretive about the specific revenue from their AI applications, let alone profits. In addition, enterprise customers are cautious about whether to pay high prices for AI services. Some conference attendees in the industry predict that widespread adoption of AI technology by enterprises may still take several years.

Debt Warnings Sounded

While the prospect for profits remains unclear, financial risks are accumulating in the AI field. Wall Street’s top investment banks have taken note of this trend and have begun to issue warnings.

Both Goldman Sachs and JPMorgan pointed out this week that debt levels among tech companies involved in the AI wave are surging. To cover the high costs of developing AI computing power, these companies are increasingly turning to credit markets. This marks a cautionary signal, indicating that during the massive investment cycle in AI, the financial leverage of some companies is being rapidly amplified, adding new uncertainties to the future market.

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