Enterprise AI Network Spending Surges Before Readiness Catches Up

By Elena Vasquez

IDC forecasts enterprise AI infrastructure spending to reach $623 billion in 2026, up 31% from 2025. Dell’Oro Group separately reported that worldwide enterprise networking revenue grew 15% year over year in the first half of 2026.

Much of the AI buildout spending comes from hyperscalers and neocloud providers, though enterprises remain buyers of core networking systems. At the ONUG AI Networking Summit, IDC analyst Leslie Rosenberg said networking was the fastest-growing category of enterprise AI infrastructure spending.

Rosenberg said servers make up the majority of IDC’s 2026 forecast. She said networking growth is concentrated primarily in data centers. IDC also sees a significant refresh in campus networks.

Mauricio Sanchez, senior director at Dell’Oro Group, joined Rosenberg on the panel. Woo Jin Ho, senior hardware analyst at Bloomberg Intelligence, moderated it. They discussed spending, budgets, readiness, workload placement and operations.

Rosenberg framed the gap between investment and execution: “What we are primarily seeing is that ambition outpaces readiness,” she said. She said it remained unclear whether enterprises were ready as organizations ramped toward spending levels forecast for 2028 through 2030.

Vendors can sell into rising budgets, but buyers may have to reverse costly purchases. Enterprises risk funding capacity before their use cases and infrastructure support are clear.

Which networking segments are growing?

Dell’Oro data show all five major enterprise networking segments posted double-digit gains in the first half of 2026. Growth accelerated in the second quarter.

• Network security
• Branch routing
• Wireless LAN
• Campus switching
• Enterprise data center switching

Dell’Oro data also show campus-switch revenue grew at a double-digit rate while port shipments were nearly flat. In the second quarter, port shipments fell 5% while average selling prices rose 19%. Dell’Oro’s market data identified DDR4 (Double Data Rate 4) memory shortages as a major source of pricing pressure. AI infrastructure buildouts had tightened component supply.

Wireless LAN followed a different path. Higher access-point shipments supported revenue as Wi-Fi 7 adoption accelerated. Enterprises also ordered ahead of expected price increases. Dell’Oro expects overall growth to moderate from the first-half pace.

Enterprise data center switching showed a similar split. Dell’Oro’s data showed front-end switching growth concentrated among large organizations. Many of those upgrades support general-purpose servers rather than dedicated AI deployments. Smaller enterprise customers continued to pull back.

Sanchez said hyperscaler figures do not translate one-for-one to the enterprise. He pointed to security tooling as an area of fast growth. He said the AI system security market was about $200 million in 2025. Sanchez expects it to reach $8 billion over the next five years.

His broader view was blunt: “So, it’s an explosive growth in pockets, but overall, it’s a very slow rising tide when it comes to the overall infrastructure spend,” Sanchez said.

Where is the AI networking budget coming from?

Both analysts said AI budgets draw on a mix of new money and reprioritization. Rosenberg said some areas have been trimmed to fund AI initiatives. She said AI and security are the two areas least subject to cuts.

Rosenberg described vendor programs designed to stretch budgets. Take-back and circularity programs let customers return equipment, receive credit and apply that credit toward a modernization purchase. She also cited zero- or low-percent financing from HPE, Juniper and Cisco. With supply chain constraints, some buyers can move ahead with recertified equipment, sometimes at a lower price.

Sanchez described customers moving workloads out of the public cloud. Some are not buying servers for an on-premises data center.

They are renting hardware in private colocation facilities instead. He said those customers cited available financial packages and uncertainty about how large AI demand would become. In his view, renting or leasing avoids locking in a capital expense over seven years of amortization.

“There are creative ways to help finance your technology initiative,” Rosenberg said.

What does AI-ready networking actually require?

Rosenberg said many organizations carry long lists of AI initiatives, but few have well-defined, viable use cases. Fewer still have confirmed that their infrastructure can support those initiatives. She identified networking and storage as the two areas with the least maturity.

Her data-center priorities started with network architecture. Rosenberg said enterprises are preparing for an 800 gigabit per second fabric. Her second priority was network security for both north-south and east-west traffic.

North-south traffic enters and leaves the data center; east-west traffic moves between systems inside it. She said teams must remediate vulnerabilities quickly once they reach the network.

Sanchez advised enterprises to build a long-term plan before buying. He pointed to tools that provide visibility into existing environments. He cautioned against spending on point products or on a platform without a plan. He said CIOs are rushing to check the AI and security boxes, creating a risk of costly zigzags.

Sanchez said his firm’s hardware surveys show enterprises in a wave of reinvestment after the pandemic. Buyers cite a need for more capacity and storage to become AI-ready. He said those requirements are not always based on clear technical criteria. Beyond coding, he said the industry is still looking for the next enterprise use case.

“I think the vendor community is doing a very good job from the infrastructure perspective to build this fear that, ‘Hey, if you don’t upgrade now, you’re going to be left behind,” Sanchez said.

Why is automation the next constraint?

Rosenberg summarized the constraint: “I just finished a whole series just specifically on networking, and one of their biggest challenges is automation,” she said. “There’s going to be a very long tail in terms of automation even before they begin to talk about AI for networking.”

Customers are consolidating data centers. They need to rationalize and automate them, then transfer knowledge to their teams.

Rosenberg described the next wave of skills: “When we’re moving into AI for networking, it’s new workflows, new operational best practices, and then once we get into infrastructure as code or network as code, that’s a whole other skill set that many are not prepared for,” she said.

“So there has to be a lot of training, use of augmented staffing, either from a third party or the vendor.”

For the spending ramp expected through 2028-2030, Rosenberg’s warning makes automation, training and staffing the nearer constraints. Dell’Oro expects overall networking growth to moderate from its first-half 2026 pace, even as buyers continue their AI buildout.