AI infrastructure expansion is the clearest demand driver for data center networking chips. As more accelerators work together on training and inference, they exchange more data across servers, racks and data centers. That raises demand for faster switching, more network capacity and higher-bandwidth interconnects—but chip demand is not the same thing as total data-center spending, and physical buildout constraints can slow deployments.
Why AI workloads need more networking
Distributed computing creates more traffic between servers
AI systems divide work among many accelerators. Those devices must exchange data as they train or serve models, generating substantial east-west traffic: communication among machines inside a data center, rather than traffic flowing between a data center and its users. As clusters grow, the network must move more data while keeping communication delays and performance variability in check.
These needs span training and inference. Marvell said in its FY2026 proxy statement that AI demand is expanding beyond training to inference. That is the supplier’s view of the market, but it illustrates why networking demand is tied not only to building large training clusters but also to deploying AI services.
Scale raises bandwidth and switching requirements
IDC describes GPU-dense “AI factories” as needing high-bandwidth, ultra-low-latency switching to sustain the east-west traffic of distributed training. In practical terms, operators need enough switching capacity to connect growing numbers of accelerators, and predictable performance so that network bottlenecks do not hold up the rest of the system. The requirements vary with the workload and architecture; they do not mean every operator will choose the same network design.
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Which networking components benefit
“Data center networking chips” covers several related but distinct parts of the infrastructure. AI buildout can support demand across these categories, but a data-center switch market figure should not be read as a direct measure of chip sales.
| Component | Role in the infrastructure | Why demand can rise |
|---|---|---|
| Ethernet switching silicon | Moves traffic through Ethernet switches in and between data-center systems. | Larger AI clusters need more capacity, and upgrades to faster ports can require new switching systems and silicon. |
| Custom networking silicon | Purpose-built chips support networking or switching functions tailored to a system or customer. | Large AI deployments can prompt investment in custom infrastructure alongside standard products. |
| Optical interconnect | Uses optical links to connect systems or carry data over longer distances. | Higher bandwidth and longer reach can make optical connections relevant within and between data centers. |
| Data-center interconnect (DCI) | Connects data centers, including regional cloud facilities. | Distributing cloud capacity across locations creates a need for high-capacity links between facilities. |
Marvell’s FY2026 annual report describes a portfolio spanning custom ASICs, interconnects and Ethernet solutions, with data-center applications including AI systems, Ethernet switching and DCI. This is a supplier’s description of its products, not independent confirmation of market demand. The categories also operate at different levels: scale-up fabrics connect tightly coupled compute within a system or rack, while scale-out networking connects systems across a broader fabric. DCI links separate data centers; it is not another name for either scale-up or scale-out.
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What market and deployment figures show—and what they do not
| Publisher and date | Reported figure or plan | How to interpret it |
|---|---|---|
| IDC, 2Q26 | The Ethernet switch market grew 43.4% year over year to $18.9 billion. | IDC attributed the growth to data-center demand from AI infrastructure investment and the transition to 800G ports. This is a switch-market result for one quarter, not a total-market estimate for networking chips. |
| Cisco, 2024 survey | 32% of surveyed organizations identified InfiniBand as their current high-performance, high-throughput choice for data-intensive workloads; 56% planned to deploy next-generation enhanced Ethernet for AI workloads. | These are survey responses about current choices and intended deployments, not global market shares or proof that planned deployments occurred. They are not a current head-to-head market comparison. |
| Cisco, 2024 survey | 47% of surveyed organizations expected a moderate or significant increase in workloads hosted in data centers, hosted cloud or colocation environments over the following two years. | This is an expectation reported during the survey period, not a measurement of subsequent workload growth. |
| NVIDIA and AWS, 2026 announcement | The companies announced plans for two million additional NVIDIA GPUs across AWS infrastructure. | The announcement is evidence of deployment intent, not confirmation that the GPUs are already deployed or a market-wide spending forecast. |
| Ciena, 2026 survey | Service providers surveyed expected managed optical fiber networks and high-capacity AI services to support revenue growth, and identified DCI as a use case. | These are respondents’ expectations published by Ciena, not realized spending or a neutral forecast for optical-chip sales. |
Switch-market revenue is useful as an indicator of infrastructure activity, but it includes systems beyond the networking silicon itself, and market definitions can differ. The available figures therefore do not establish a current total-market estimate for data-center networking chips.
How operators choose a network architecture
Ethernet or InfiniBand
The choice depends on the target workload, cluster scale and operating environment. Buyers may weigh ecosystem and interoperability, performance and congestion behavior under their workloads, staff expertise, total system cost and supplier availability. Cisco’s 2024 survey documents reported use and plans at that time; it does not establish a universal winner or current market shares.
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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.
- SILENT & ENERGY-EFFICIENT OPERATION: Fanless design ensures silent performance, while IEEE 802.3az Energy Efficient Ethernet reduces power consumption without compromising high-speed network performance.
- REGIONAL COMPATIBILITY: Made for use in U.S. & CA only
Electrical or optical links
Electrical and optical interconnects involve trade-offs in reach, bandwidth, power, cost, latency and deployment complexity. Optical links are relevant where bandwidth and distance requirements call for them, including connections between regional cloud data centers. The cited sources do not provide a neutral, current quantitative comparison showing that one approach is best across deployments.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Why announced demand may not become immediate chip demand
Networking equipment is only one part of building an AI data center. In an SEC filing, NVIDIA identified land, power, data-center shells and capital as crucial to customers’ ability to complete buildouts, and said shortages could affect its business. If any of these inputs delays a project, orders for networking systems and their chips can also be deferred or reduced.
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- Reliable and Quiet-IEEE 802.3X flow control provides reliable data transfer and Fanless design ensures quiet operation
- Plug and Play-Easy setup with no software installation or configuration needed
- Advanced Software Features-Prioritize your traffic and guarantee high quality of video or voice data transmission with Port-based 802.1p/DSCP QoS and IGMP Snooping
Announcements from NVIDIA and AWS, and Meta’s announced AI infrastructure plans and adoption of NVIDIA Spectrum-X Ethernet, are examples of deployment activity and demand intent. NVIDIA and Meta describe Spectrum-X as offering predictable, low-latency performance and operational and power efficiency in Meta’s infrastructure; those are vendor claims, not independent measurements that apply to every installation. Announced plans should not be mistaken for completed deployments or a total of market-wide capital spending.
Other factors worth examining when assessing the durability of demand include whether customers see returns on AI investment, how fully installed equipment is used, competing architectures, supplier capacity and the pace of future spending. The cited evidence does not quantify how strongly these factors may raise or reduce networking-chip demand.
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- TRAFFIC OPTIMIZATION: Supports IEEE 802.3x flow control and advanced traffic optimization technology to reduce data bottlenecks and ensure smooth, efficient data transfer across your network
What the evidence means for the demand outlook
The strongest supported conclusion is directional: AI cluster expansion increases the need for networking capacity, and current market and company evidence points to activity across Ethernet switching, custom networking, optical interconnect and DCI. But the available market figure covers Ethernet switches, while company announcements and surveys measure different things. None should be treated as a comprehensive forecast for networking-chip sales.
For readers evaluating the trend, keep three measures separate: announced AI deployments, reported switch-market revenue and actual networking-silicon demand. They are related signals, but they are not interchangeable.
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