Demand for data center networking chips is being driven most clearly by the expansion of AI infrastructure. As more accelerators work together across servers and racks, they need faster, higher-capacity connections to exchange data. That pushes demand for switching silicon, custom networking components and optical interconnect—but the pace of actual deployments depends on whether operators can secure the power, facilities and capital to build them.
Why AI workloads need more networking
AI training is distributed across many accelerators rather than performed by one processor in isolation. Those accelerators continually exchange data with one another and with other systems, creating substantial east-west traffic—traffic moving among servers inside a data center. Inference also adds demand as AI services are deployed beyond training environments.
When clusters grow, the network must move more data while maintaining enough switching capacity, bandwidth and predictable low latency to keep the connected systems working effectively. A network that cannot keep pace can constrain the value of the compute capacity around it. The exact requirements depend on the workload and system design; not every operator uses the same architecture.
IDC attributed growth in the Ethernet switch market to AI infrastructure investment and the transition to 800G ports. In IDC’s 2Q26 market report, Ethernet switch revenue grew 43.4% year over year to $18.9 billion. That figure describes the Ethernet switch market for that quarter—not the total market for networking chips. Switch-system revenue includes more than semiconductor silicon, and market definitions differ.
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Which parts of the network benefit?
“Data center networking chips” covers several related but distinct parts of infrastructure. Demand can reach the silicon that moves traffic through switches, custom networking silicon designed for specific systems, and components that connect equipment electrically or optically. Data center interconnect (DCI) links separate data centers, including regional cloud facilities.
Ethernet switching silicon
Switch chips direct traffic between connected systems. More servers, accelerators and ports—and transitions to higher port speeds—can increase demand for switching capacity. Ethernet switch-market growth is a useful signal of infrastructure investment, but it is not a direct measure of chip sales.
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Custom networking silicon and scale-up fabrics
Some systems use custom-designed chips or switch fabrics to connect compute components for a particular platform or workload. Marvell’s FY2026 annual report describes a portfolio spanning custom ASICs, interconnects and Ethernet solutions, and says it is developing switch fabrics for AI scale-up demands. This is a supplier’s description of its products and development, not an independent measure of market demand.
Scale-up refers to tightly connecting compute within a system or rack. Scale-out refers to connecting systems across a broader network fabric. The terms describe different networking needs; they are not interchangeable.
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- PLUG-AND-PLAY UNMANAGED NETWORK SWITCH: Simple plug-and-play setup with no software to install or configuration required.
- FLEXIBLE MOUNTING OPTIONS: Compact metal design supports desktop or wall-mount placement for versatile installation.
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- REGIONAL COMPATIBILITY: Made for use in U.S. & CA only
Optical interconnect and data center interconnect
Electrical and optical connections serve different parts of data center infrastructure. Optical interconnect can support high-bandwidth links within and between systems, while DCI connects separate facilities. Marvell’s annual report describes transceiver technology for interconnecting regional cloud data centers. Ciena’s 2026 survey reported service-provider expectations that managed optical-fiber networks and high-capacity AI services could support revenue growth, and identified DCI as a use case. Those are survey respondents’ expectations, not confirmed spending or realized revenue.
What deployment announcements tell us—and what they do not
Large cloud and technology companies have announced plans that illustrate the scale of investment intent. NVIDIA and AWS announced plans for two million additional NVIDIA GPUs across AWS infrastructure, alongside work involving AI factories, networking and other infrastructure. Meta announced AI infrastructure plans that include NVIDIA systems and adoption of NVIDIA Spectrum-X Ethernet.
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These announcements point to potential demand for the networks needed to connect large AI systems. They do not establish that all the announced capacity is already deployed, quantify a market-wide spending total, or prove that every operator will choose the same networking products.
Ethernet and InfiniBand: what the available survey shows
Ethernet and InfiniBand are both architectural options for high-performance data center networking. Selection depends on the target workload, performance and congestion behavior, scale, operational expertise, system cost and supplier availability. The available survey figures offer a dated view of organizational responses, not a current market-share comparison or proof of a universal winner.
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| Measure | Reported result | How to interpret it |
|---|---|---|
| Current choice for data-intensive workloads | 32% of organizations surveyed by Cisco in 2024 identified InfiniBand as their current high-performance, high-throughput choice. | A survey response, not InfiniBand’s share of the global market. |
| Planned networking for AI workloads | 56% of organizations surveyed by Cisco in 2024 planned to deploy next-generation enhanced Ethernet. | A reported plan, not a completed deployment. |
The survey also found that 47% of respondents expected a moderate or significant increase in workloads hosted in data centers, hosted cloud or colocation environments over the following two years. That is an expectation reported during Cisco’s 2024 survey period, not a measured outcome or a forecast of chip sales.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What can slow demand?
Announced AI demand does not translate automatically into completed data center capacity or networking purchases. NVIDIA’s SEC filing identifies land, power, data center shells and capital as crucial to customers’ full buildout, and says shortages could affect its business. If a facility cannot be built or powered on schedule, the associated network deployment can also be delayed.
Other factors worth assessing include whether customers earn sufficient returns on AI investment, how fully installed equipment is used, whether alternative architectures meet workload needs, supplier capacity and the timing of spending cycles. The evidence cited here does not quantify how much any of these factors changes overall networking-chip demand.
Quick Recap
How to read demand signals without overclaiming
- Keep the market category straight. Ethernet switch revenue is not the same as networking-chip revenue or total data center investment.
- Separate plans from deployments. Announced GPU and infrastructure plans indicate intent; they do not show that the planned capacity is already online.
- Check the source and date. IDC’s 2Q26 figure covers a defined switch market and quarter. Cisco’s 2024 figures are survey responses, while supplier reports and announcements describe the companies’ own products, plans or views.
- Watch physical buildout conditions. Power, land, facilities and capital affect how quickly planned compute can become operating infrastructure.
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
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