Edge computing centers are set to overtake centralized data centers as the main location for the world’s data processing, an outflow driven by surging demand in artificial intelligence (AI)-based low-latency applications and a growing need for localized content, which could be a boon for telecommunication operators and forward-looking data center providers.

ReThink Technology Research predicts 74% of data will be processed outside of traditional data centers in “various layers and hierarchies” by early in the next decade, with more than 50% of that data processed “right at the edge.” That migratory push will see that data processing flee those centralized data centers, which currently process around 90% of the world’s data.

The report explains that those edge locations “could be in telco offices at fiber termination points for fixed networks, or base stations for mobile networks.”

ReThink also noted that growing adoption of open radio access networks (RAN) architectures by telecom operators will boost the need for edge data processing. This will be based on the connected use of the RAN intelligent controller (RIC) framework that uses non-real-time (xApps) and near-real-time (rApps) to fine-tune RAN optimization based on demand.

This data processing outflow will power new revenue streams that are forecast to rise from $3.29 billion this year to nearly $29 billion by 2031. This will be split evenly between operator and enterprise deployments.

“Several trends are conspiring to drive this growth,” the ReThink report explains. “The underlying one being the increasing distribution of computing toward the edge of networks, fixed or wireless, from monolithic data center architectures.”

ReThink’s report echoes similar positive financial forecasts tied to edge data center deployments.

IDC recently predicted spending on edge computing will hit $228 billion this year, which is a 14% increase compared to 2023. That growth is expected to push overall spend to nearly $378 billion by 2028.

IDC’s numbers include enterprise and service provider spending on hardware, software, professional services, and provisioned services for edge solutions. The analyst firm also tags the edge as “technology-related actions outside of centralized data centers, serving as an intermediary between connected endpoints and the core IT environment.”

Similar to ReThink, IDC tagged that connectivity position as becoming increasingly important in the wake of the growing push around AI and generative AI (genAI).

“As the focus of AI shifts from training to inference, edge computing will be required to address the need for reduced latency and enhanced privacy,” Dave McCarthy, research VP for cloud and edge services at IDC, wrote. “This trend not only optimizes operation efficiencies but also fosters new business models that were previously not possible with centralized infrastructure. Distributing applications and data to edge locations enables faster decision-making with reduced network congestion.”

This edge enthusiasm was cautiously echoed by Technology Business Research (TBR), which estimates the enterprise edge market will grow at a nearly 20% compound annual growth rate (CAGR) over the next several years to surpass more than $90 billion in revenues by 2027. The firm expects professional and managed services to be the fastest segment growers at a more than 23% CAGR, with software growing at just under 20% CAGR.

TBR added that the broader tightening of IT spend is reining in investments, but the “deceleration of growth in the edge market will not be as severe as in other markets due to the strategic nature of edge investments.”

Who benefits from the edge opportunity? ReThink noted that mobile telecommunication operators were positioned to reap financial benefits from edge investments based on their ability to leverage embedded infrastructure and by taking advantage of new cloud-based technologies.

“It is important that operators are actively engaged in the march to edge compute, with strategies designed to capitalize on the opportunities both for efficiency improvements with connected energy savings, and new services around associated network APIs,” the firm explained. “The latter will allow third parties to access and manipulate service features.”

Carriers have for years been touting their aspirational position within the edge ecosystem, a claim that is gathering further AI-powered momentum.

T-Mobile US recently noted it sees a cloud-based revenue opportunity tied to its future-looking push of bolstering its network with AI to support edge components of its RAN architecture. These updates will turn those locations into edge data centers or cloud connections that can in turn better serve AI workloads.

“These kinds of AI workloads will increasingly demand that processing have happen on the device, which we’re starting to see but there are obvious limitations there, or on a cloud near the device, and that’s a business opportunity that we see in the future,” T-Mobile US CEO Mike Sievert said during a recent investor conference, adding that “we do see that running third-party AI workloads in our magenta cloud near the customer endpoint may be something that we can add value to the world with. There’s nothing in our contract about this because that cloud would be ours, not belonging to our partners, and so what we would be doing is assembling the network technologies to do it in the future.”

That “contract” reference is tied to T-Mobile US’ current work with cloud hyperscalers like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP), which could also be part of this still evolving process.

“We would be very open minded about partnering if there’s a way we can,” Sievert explained. “We’re a deep partner with all three, probably deepest with Microsoft Azure, but we’re also work deeply with AWS, we work with GCP, those are the scaled providers. And you saw we are working with OpenAI that right now all the workloads are processed in Azure, but they’re a close partner. There’s lots of flexibility here and if we can add value to our partners and have joint productization and go to market in the future, that’s one area to explore. But that’s pretty speculative at this point.”

Verizon CEO Hans Vestberg has made similar comments over the years in touting that’s carrier’s multi-access edge compute (MEC) strategy.

“The loads are coming,” Vestberg said during the Goldman Sachs Communacopia + Technology Conference. “Probably it’s going to take some time because the majority of genAI today is large language models that you’re training, so they send them way back to the data centers. But as soon as they start doing, like Verizon, it’s an application that you use, then you want it closer to the customer because of transport costs, security, [and] in certain cases, latency.”

Vestberg also boasted of Verizon’s long-standing partnerships with all three of the nation’s largest hyperscalers to boost its edge posture.

“We have processing, compute, storage, power already built across the nation with our mobile edge compute, so I think that no one in the telco world is better prepared than Verizon to be part of the genAI edge compute of the time,” Vestberg said.

TBR noted that those hyperscalers also had an inside line toward gaining a financial benefit from the edge opportunities, specifically citing efforts like Google’s air-gapped Distributed Cloud push and Amazon Web Services’ (AWS) Local Zones.

“With their vast access to data, the hyperscalers will be a natural choice for customers that do not want to move their genAI solutions to a separate compute ecosystem but want to process the data closer to the point of use,” TBR added.