AI’s capital supercycle means big spend, bigger returns

Jeff Johnston

April 8, 2026

Key Points

• Capital expenditures on AI are exploding, and they are creating real shareholder value.
• The artificial intelligence spending cycle is not over. In fact, it may be accelerating based on feedback from the AI infrastructure ecosystem.
• Risks exist, but today’s market lacks the excess capacity and frothy valuations of the dot-com era.

AI-related capital expenditures are reaching unthinkable levels as hyperscalers such as Amazon, Microsoft, Meta and Google race to build next-generation technologies that will profoundly impact how we live and work. For example, in 2024, U.S. hyperscalers spent an estimated $235 billion on artificial intelligence. In 2025, that figure climbed to $400 billion, and in 2026, hyperscalers will likely spend close to $700 billion.

AI-related CapEx is not only impacting U.S. GDP, but it is also a driving force behind the recent rise in stock prices. The highly concentrated nature of this capital spend — and the outsized impact it is having on financial markets —is fueling concerns that any slowdown in spending could burst the proverbial AI bubble. This concern has merit, but a closer look at the profitability of this spend, along with broad feedback from across the AI ecosystem, suggests this CapEx cycle has yet to fully play out.

To make sense of this, a simple question to ask is: Is this level of CapEx a good thing for the hyperscalers? In other words, are they creating value for shareholders? The way to answer that question is by examining return on invested capital (ROIC). If ROIC is rising alongside increased CapEx, then the answer is yes, these investments are creating shareholder value. That is exactly what is happening today. Given that, one can reasonably conclude this CapEx cycle may not be over.

Additionally, examining the broader AI infrastructure ecosystem suggests spending levels should remain healthy for the foreseeable future. Take Nvidia for example, it recently announced a line of sight to over $1 trillion in revenue for its AI GPU chipset business through the end of 2027, a massive increase from the $130 billion the company generated in fiscal year 2025. One can also look at memory maker Micron, whose products are integral to the AI CapEx cycle. The company recently reported second quarter revenue of $23 billion, a staggering 196% increase year over year and well above investor expectations. Micron also guided third quarter revenue to $33.5 billion.

The point is that companies across the AI supply chain are delivering mind-blowing results, and their forward guidance suggests AI spending could continue to accelerate.

On the risk side, stakeholders with long memories have compared today’s environment with the 2000 dot-com recession. We do not believe that is a fair comparison. In 2000, excess capacity was the primary culprit that brought the market down, whereas today there is no such excess capacity in the AI infrastructure market. Additionally, valuations were higher in the dot-com era, and today’s AI companies have much healthier cash flows and existing revenue streams as compared to the tech companies in 2000.

One area of concern, however, is the increasingly circular nature of deals between major AI ecosystem players. These companies are becoming more interdependent, raising the question: If one company fails to meet its obligations, could that trigger a broader, contagious event across the market? It is possible, but for now it feels more likely to result in isolated disruptions rather than systemic risk.