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How enterprise networks need to change for AI agents

Networking in the age of AI

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Key Points

What is changing

The article “Network evolution for the Agentic AI era” from Network World explains that AI agents create constant demand, turning always on traffic into a reality that requires real-time telemetry and segment routing. Without this visibility, operators must rely on stale reports that can miss microsecond-level changes. Static reports are often outdated by the time they are used, so real-time telemetry is essential. Operators also need to monitor latency spikes in real time to avoid service degradation. Continuous monitoring helps align performance with AI service level objectives. This proactive approach reduces unexpected outages.

Network architects are moving from rigid IP designs to FlexAlgo capabilities that support EVPN and MACsec, enabling paths that match latency, bandwidth, or resiliency needs. Segment routing also reuses existing hardware, making the transition smoother. The new approach lets teams define performance objectives and let the network adjust paths automatically, reducing manual tunnel setup.

Why it matters

These advances matter most for large enterprises that need to enforce policy, meet SLA targets, and run AI workloads alongside traditional services, often in regulated sectors like healthcare and finance. They also must manage data sovereignty and strict compliance rules, which adds another layer of complexity.

For network engineers this means updating routing policies, monitoring FlexAlgo settings, and applying any required security patches as the new stack replaces older IP models, which can be a major shift for legacy environments. This may require teams to retrain staff and update documentation, extending the rollout timeline.

Share your experience deploying these networks in the comments and let others learn.

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