Data centers are set for an artificial intelligence (AI) boost that could see investments surge past $1 trillion over the next several years, with that investment also spilling over into the connectivity tissue linking those locations.

Dell’Oro Group predicts data center capex will surge to a 24% compound annual growth rate (CAGR) by 2028 due to “surging demand in AI-related data center infrastructure.” This could result in a 13-figure market over the next several years.

“AI has the potential to generate more than a trillion dollars in AI-related infrastructure spending in cloud and enterprise data centers over the next five years,” Baron Fung, senior research director at Dell’Oro Group, wrote. “AI infrastructure, which includes servers with GPU or custom accelerators, along with dedicated networking, storage, and facilities, are highly capital-intensive. While the industry continues to assess the potential return on AI-related investments, major efforts have been underway in the ecosystem in achieving long-term sustainable capex growth.”

The research firm noted that U.S.-based hyperscalers like Amazon, Google, Meta, and Microsoft will drive much of this investment, with just those four firms accounting for half of global data center capex as early as 2026.

Those hyperscalers have increasingly hinted at this need to increase their AI-connected investments.

“We are – and we've talked about now for quite a few quarters – we are constrained on AI capacity,” Microsoft CFO Amy Hood said during Microsoft’s latest earnings call. “And because of that … we've … signed up with third parties to help us as we are behind with some leases on AI capacity. We've done that with partners who are happy to help us extend the Azure platform, to be able to serve this Azure AI demand. And you do see us investing quite a bit as we've talked about in builds so that we can get back in a more balanced place.”

However, they also remain cognizant of how they manage that investment.

Amazon CEO Andy Jassy, during the company’s second-quarter earnings call, acknowledged that it’s important to have enough capacity in place to support growing AI-infused data center traffic, but “if you actually deliver too much capacity, the economics are pretty woeful and you don't like the returns of the operating income.”

“The reality right now is that while we're investing a significant amount in the AI space and in infrastructure, we would like to have more capacity than we already have today,” Jassy added. “I mean we have a lot of demand right now. And I think it's going to be a very, very large business for us.”

ABI Research noted in a report that this AI-fueled investment spree will also angle toward “large and mega-sized colocation facilities.” The firm noted that 28% of total worldwide data centers currently fit this size definition, but that “number will grow to 43% by 2030 as companies build larger data centers that can accommodate AI/generative AI workloads and other data-hungry applications.”

Where is this AI growth coming from?

Research firm ISG noted in a new report that the average large enterprise is planning to nearly double their number of AI-enabled applications by the end of this year. This will see that average grow from 250 applications that were AI-enabled at the end of 2023, to 488 AI-enabled applications by the end of 2024.

Connecting and constructing more data centers

This investment boom is also expected to power new data center connectivity needs.

Lumen Technologies CTO Dave Ward explained to SDxCentral that this surge in data center usage will require a bolstered network architecture.

“There's so many capacity constraints associated with constructing AI: power, literally power from the grid, and then where you can place your data center, can you get the GPUs?” Ward said. “This network capacity is a very scarce resource, in particular, to where the data centers or AI data centers are being built.”

Analyst firm LightCounting, for instance, predicts growing AI use will result in a doubling of sales this year for Ethernet optical transceivers used in AI clusters.

“What this means for us as a connectivity partner is we fully plan on building an AI fabric between these locations and major data centers that are of the right power, size, scale, to host GPUs and the AI workloads and create a specialized connectivity fabric just for that purpose,” Ward said of this effort.

“So much fiber and so many waves are required, and that segment has really become a different segment than some of the other cloud economic segments that are coming in that we can construct just to that.”