Common sense suggests that any supplier of goods or services is at risk when the customer base is highly concentrated. Indeed, we might argue that buyer diversification is a core strategic objective for any supplier of goods or services.
Unfortunately, high customer concentration is a basic feature of high-performance computing as a service, leading to high concentration on the supply side as well. And that leads to a high concentration of earnings growth in public markets as well.
Perhaps few like this state of affairs, as it increases market risk for just about everyone in the investing value chain. But it really cannot be helped.
Customer concentration, often defined as having a single customer represent 10 percent or more of revenue, or top three to five customers representing 30 percent to 50 percent of sales, creates vulnerabilities:
The "single point of failure" (revenue shock if a key buyer defects)
Squeezed profit margins (buyers know they have leverage)
Asymmetric counterparty and credit risk if a single buyer defaults
Operational and capacity misallocation to the few large buyers
Higher cost of capital, as lenders and equity investors view customer concentration as a risk.
But the current artificial intelligence infrastructure market is skewed to a few customers supplying high-performance computing as a service (Google, Amazon Web Services, Azure, Oracle, SpaceXSI)
At the same time, the AI infrastructure boom is producing:
A relatively small group of companies capturing a disproportionate share of incremental earnings growth in the public equity market
A similarly small group of hyperscalers responsible for a large share of demand for advanced AI computing infrastructure.
Micron alone accounts for 19 percent of all earnings growth in the S&P 500 in the third quarter of 2026 and Nvidia accounts for 15 percent, for example. That’s earnings growth, not the share of total market earnings.
Goldman analysts say the top 10 contributors account for approximately 68 percent of growth. So Goldman estimates that AI infrastructure companies (excluding hyperscalers) will account for 54 percent of third-quarter earnings growth.
Hyperscalers will contribute another 19 percent. Together, AI infra suppliers and hyperscalers account for 73 percent of earnings growth.
That will worry just about everyone. But such concentration reflects scale economics in the frontier AI model part of the value chain; the inference as a service value chain and the AI infra value chain.
There arguably are several reasons why the concentration exists:
scale economies favor large buyers
capital access matters
utilization matters
complementary assets matter.
Such characteristics are common in capital-intensive industries such as telecommunications, aerospace, semiconductor fabrication and electricity generation.
In some sense, we might argue that concentration is a feature, not a bug. That is not to discount the risks. Everything hinges on eventual outcomes across the economy, especially the ability of the frontier model developers and computing as a service suppliers to demonstrate economic value for their costumers, leading to subsequent revenue growth for the hyperscalers.
So concentration, in and of itself, is not itself a reason to reject the AI infrastructure opportunity. Many other successful industries also are capital intensive and concentrated on the buyer and supplier sides.
But such concentration also does magnify risk. A spending slowdown by the hyperscalers will disrupt market valuations of firms in the industry.
The wisdom of current investment pacing will be determined by the return on the capital being deployed, of course.
But buyer or supplier concentration, in and of itself, is not necessarily a bug. It is a feature of some industries, where scale economies are required.
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