Key Points
- 34% of AI-related network traffic growth in campus and branch environments over the past year
- 73% of organizations expect capacity constraints within two years due to AI demands
- East-west traffic and security gaps challenge existing network infrastructure
What is changing
AI adoption is creating unpredictable traffic spikes in enterprise networks. A Cisco survey found that 34% of AI-related traffic now flows through campus and branch networks, up sharply in the past year. This traffic is set to grow 209% over three years, overwhelming systems built for steady SaaS or CRM workloads. Most networks struggle to handle the surge, especially as AI agents communicate more with each other and internal systems.
The report highlights that east-west traffic – data moving between internal systems – has jumped 67% due to AI workloads. At the same time, 80% of organizations say AI has expanded their attack surface, raising security risks. Many IT teams lack visibility into what AI tools are actually running on their networks, complicating monitoring and control.
Why it matters
This matters most to network engineers and IT admins managing campus and branch infrastructure. They may notice slower network performance, security blind spots, or delays in deploying AI tools. The issue is especially urgent for organizations planning to scale AI beyond pilot phases, as 93% of IT leaders are already speeding up network upgrades.
The practical takeaway: Networks need upgrades to handle AI traffic, better security tools, and improved observability to track AI workloads. Without these changes, 61% of companies may delay AI projects. This is a major concern for enterprises aiming to stay competitive, as AI infrastructure now requires attention beyond data centers. Share your network challenges with AI adoption in the comments below.
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