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IDC: AI workloads driving high-speed Ethernet switch adoption

The high-end Ethernet switch market is getting a boost from cloud providers and enterprises that are preparing their data centers for AI workloads. Meanwhile, high-end router sales are slowing, according to IDC’s most recent quarterly t…

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The high-end Ethernet switch market is getting a boost from cloud providers and enterprises that are preparing their data centers for AI workloads. Meanwhile, high-end router sales are slowing, according to IDC’s most recent quarterly trackers.





Compared to a year ago, the Ethernet switch market and router market both declined in the second quarter; Ethernet switching fell 14% and the router market declined 31% compared to the second quarter of 2023, according to IDC’s numbers. But there were some segments that achieved moderate to strong growth, said Brandon Butler, IDC senior research manager, enterprise networks. “For example, the data center portion of the Ethernet switch market rose 8%” year over year, Butler said. Even more significantly, revenues for the highest speed Ethernet switches that IDC tracks – 200/400 GbE – doubled from 2Q23 to 2Q24, climbing 104%, Butler said.





In the data center segment of the market, enterprises and service providers are investing in ever-faster Ethernet switch speeds to support rapidly expanding AI workloads, Butler said.





“AI, and particularly generative AI, is a major growth driver in data center Ethernet switching,” Butler said. The research firm is forecasting growth in the generative AI data center Ethernet switch market from $640 million in 2023 to more than $9 billion in 2028, “a 70% five-year compound annual growth rate,” he said.





“This is further evidenced in the outsized growth in the highest speed Ethernet switches (200/400GbE +104% y/y in 2Q24),” Butler said. “The Generative AI Datacenter Ethernet Switch market is driven predominantly by hyperscale cloud providers building high-speed Ethernet switch capacity to support GenAI workloads now, but other cloud providers and enterprise deployments of Ethernet switching will contribute to the market’s growth going forward, too,” Butler said.





The non-data-center segment of the Ethernet switch market, which includes Ethernet switches typically deployed in enterprise campus and branch locations, declined 28.9% year over year, but increased 15.0% compared to the first quarter of 2024. The annualized decline was driven in part by challenging comparisons with the year-ago quarter, which had historically high revenues driven by product backlog outlays resulting from the market challenges of the pandemic.  





“By comparison, the non-GenAI Datacenter Ethernet switch market will grow at a low single digit CAGR from 2023-2028. But the broader Datacenter Ethernet Switch market is a diverse market: On-prem traditional DC deployments will be declining, enterprise private clouds will grow moderately, and public cloud deployments (outside of GenAI) will continue to show solid growth,” Butler said.





SD-WAN impacting enterprise router market





Meanwhile, the enterprise router market is in a state of transition, as it is being subsumed to some degree into SD-WAN with its software and cloud-based deployments, according to Butler.





“While the enterprise router market will decline over the five-year forecast period, the SD-WAN market is set to grow by a more than 9% CAGR to reach $8.1 billion by 2028,” Butler said.





Different trends are impacting the service provider (SP) routing market, Butler noted. “SP routing is down quite a bit this year because of weak spending by [communications service providers] in general that is impacting many different SP networking markets, including the SP Routing. We expect the market to remain weak for another quarter or two and then rebound in 2025,” Butler said.


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SOC Incident Playbook: Vulnerability Remediation & Verification
Syntax validiert (0 Fehler)
title: Detect Exploitation - IDC: AI workloads driving high-speed Ethernet switch adoption
id: ea611db7-e96d-4a6d-96f9-f0ef8d8bf6af
status: experimental
description: Automatisch generierte SIEM-Erkennungsregel basierend auf CTI Intelligence
references:
  - https://tsecurity.de/
author: iShareStuff CTI Automated Detection Engine
date: 2026-09-25
logsource:
  category: network_connection
  product: any
detection:
  selection:
      CommandLine|contains:
        - 'exploit'
  condition: selection
falsepositives:
  - Legitime administrative Zugriffe oder Penetrationstests
level: high
tags:
  - attack.initial_access
Syntax validiert (0 Fehler)
rule CTI_Threat_Indicator {
    meta:
        author = "iShareStuff CTI Automated Detection Engine"
        date = "2026-09-25"
        description = "YARA Signature for "
    strings:
        $str = "IDC: AI workloads driving high" ascii wide
    condition:
        any of them
}
Syntax validiert (0 Fehler)
index=security sourcetype IN ("cisco:asa", "pan:traffic", "zeek_conn", "suricata", "WinEventLog:Security")
("IDC AI workloads driving high-speed Ethe")
| stats count earliest(_time) as first_seen latest(_time) as last_seen by src_ip, dest_ip, dest_host, signature
| eval first_seen=strftime(first_seen, "%Y-%m-%d %H:%M:%S"), last_seen=strftime(last_seen, "%Y-%m-%d %H:%M:%S")
| sort - count
Syntax validiert (0 Fehler)
message: "*IDC AI workloads driving high-speed Ethe*"
Syntax validiert (0 Fehler)
CommonSecurityLog
| where Message has "IDC AI workloads driving high-speed Ethe"
| summarize EventCount = count(), FirstSeen = min(TimeGenerated), LastSeen = max(TimeGenerated) by SourceIP, DestinationIP, DestinationPort, Activity
| extend DetectionRule = "iShareStuff-CTI-Compiled"
| sort by EventCount desc

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CTI Threat Relationship Graph2 Knoten / 1 Relationen
CVE / Incident Software MITRE ATT&CK CWE Weakness IoC
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Reconnaissance
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Resource Development
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Initial Access
Execution
Persistence
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Privilege Escalation
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Discovery
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Lateral Movement
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Collection
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Command and Control
Exfiltration
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Impact
tsecurity.de Cognitive Threat RAG
Fokus-Vektor:

Kognitive Analyse für identifizierte Bedrohung: Erhöhte Bedrohungslage im Bereich IDC: AI workloads driving high-speed Eth.... Basierend auf 368k Vektor-Korrelationen werden sofortige Isolationsmaßnahmen für betroffene Endpunkte empfohlen.

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